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id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Bhupendra Fataniya</h3></div><div class="js-work-strip profile--work_container" data-work-id="122922701"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/122922701/Automated_Digitization_of_Student_s_Marks_from_the_Answer_Book_Images_Using_a_Lightweight_CNN_Model"><img alt="Research paper thumbnail of Automated Digitization of Student’s Marks from the Answer-Book Images Using a Lightweight CNN Model" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/122922701/Automated_Digitization_of_Student_s_Marks_from_the_Answer_Book_Images_Using_a_Lightweight_CNN_Model">Automated Digitization of Student’s Marks from the Answer-Book Images Using a Lightweight CNN Model</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://niruni.academia.edu/rutulpatel">rutul patel</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://nirmauni.academia.edu/BhupendraFataniya">Bhupendra Fataniya</a></span></div><div class="wp-workCard_item"><span>SN Computer Science</span><span>, 2024</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Preparing student’s digital marksheet using images of student answer-books is a potential applica...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Preparing student’s digital marksheet using images of student answer-books is a potential application in academic institutions. Segmenting assigned marks automatically from answer-book images is extremely challenging, and it also demands pre-processing before the recognition stage. In addition, recognizing handwritten digits is crucial due to different writing styles. Existing research admits the superior performance of deep learning-based models in handwritten digit recognition (HDR) applications for popular datasets. However, their implication on real-time data for an experimental setup needs much attention. This paper presents an experimental setup that uses student answer-book images to record students’ marks digitally. We proposed a lightweight convolutional neural network (CNN) model for HDR. We also introduced a contour-based segmentation process for automatically extracting student details from answer-book images. The obtained results show the state-of-the-art performance of our proposed CNN model for real-time images. Further, introducing additional pre-processing before recognition significantly enhances the accuracy of the HDR experimental setup.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="122922701"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122922701"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122922701; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=122922701]").text(description); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="92525308"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/92525308/Real_Time_Object_Detection_in_Microscopic_Image_of_Indian_Herbal_Plants_using_YOLOv5_on_Jetson_Nano"><img alt="Research paper thumbnail of Real-Time Object Detection in Microscopic Image of Indian Herbal Plants using YOLOv5 on Jetson Nano" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/92525308/Real_Time_Object_Detection_in_Microscopic_Image_of_Indian_Herbal_Plants_using_YOLOv5_on_Jetson_Nano">Real-Time Object Detection in Microscopic Image of Indian Herbal Plants using YOLOv5 on Jetson Nano</a></div><div class="wp-workCard_item"><span>2022 International Conference on Connected Systems &amp; Intelligence (CSI)</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="92525308"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="92525308"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 92525308; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=92525308]").text(description); $(".js-view-count[data-work-id=92525308]").attr('title', description).tooltip(); 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</script> <div class="js-work-strip profile--work_container" data-work-id="92525307"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/92525307/Shape_Features_based_classification_of_Herbal_Plants_from_its_Powder_using_Microscopic_Image"><img alt="Research paper thumbnail of Shape Features based classification of Herbal Plants from its Powder using Microscopic Image" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/92525307/Shape_Features_based_classification_of_Herbal_Plants_from_its_Powder_using_Microscopic_Image">Shape Features based classification of Herbal Plants from its Powder using Microscopic Image</a></div><div class="wp-workCard_item"><span>Journal of image processing & pattern recognition progress</span><span>, Sep 24, 2018</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="92525307"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="92525307"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 92525307; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=92525307]").text(description); $(".js-view-count[data-work-id=92525307]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 92525307; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='92525307']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=92525307]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":92525307,"title":"Shape Features based classification of Herbal Plants from its Powder using Microscopic Image","internal_url":"https://www.academia.edu/92525307/Shape_Features_based_classification_of_Herbal_Plants_from_its_Powder_using_Microscopic_Image","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="92525305"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/92525305/Innovations_in_evaluation_An_integral_part_of_outcome_based_education"><img alt="Research paper thumbnail of Innovations in evaluation: An integral part of outcome based education" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/92525305/Innovations_in_evaluation_An_integral_part_of_outcome_based_education">Innovations in evaluation: An integral part of outcome based education</a></div><div class="wp-workCard_item"><span>2015 5th Nirma University International Conference on Engineering (NUiCONE)</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Education in India in 21st century demands innovations in the evaluation methods with the emergen...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Education in India in 21st century demands innovations in the evaluation methods with the emergence of Outcome Based Education (OBE). Lots of Research is already done in innovations in teaching and learning methods, but very few literatures on the innovations in evaluations are available. The paper discusses various innovative methods for the evaluation of students. The pros and cones of traditional exam and the new methods are also discussed. A survey on the various method is carried out and the results of the same are also presented.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="92525305"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="92525305"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 92525305; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=92525305]").text(description); $(".js-view-count[data-work-id=92525305]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 92525305; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='92525305']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=92525305]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":92525305,"title":"Innovations in evaluation: An integral part of outcome based education","internal_url":"https://www.academia.edu/92525305/Innovations_in_evaluation_An_integral_part_of_outcome_based_education","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="77832138"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/77832138/Microscopic_Image_Analysis_Method_for_Identification_of_Indian_Herbal_Plants"><img alt="Research paper thumbnail of Microscopic Image Analysis Method for Identification of Indian Herbal Plants" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/77832138/Microscopic_Image_Analysis_Method_for_Identification_of_Indian_Herbal_Plants">Microscopic Image Analysis Method for Identification of Indian Herbal Plants</a></div><div class="wp-workCard_item"><span>2014 International Conference on Devices, Circuits and Communications (ICDCCom)</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Identification of medicinal plant from its powder is a common task performed in pharmaceutical la...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Identification of medicinal plant from its powder is a common task performed in pharmaceutical labs and industries. In this paper, we are proposed a identification using machine intelligence. The algorithm is designed for the microscopic images of plant powder and segment the specific object from these images. From the extracted image unique features are identified and using this we train our algorithm and classify the test images. We have prepared the image database at our pharmacy lab for two plants namely Licorice and Kurchi plant. The proposed algorithm is applied on the variety of fifty images and results are described using confusion matrix and ROC curves.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="77832138"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="77832138"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 77832138; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=77832138]").text(description); $(".js-view-count[data-work-id=77832138]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 77832138; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='77832138']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=77832138]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":77832138,"title":"Microscopic Image Analysis Method for Identification of Indian Herbal Plants","internal_url":"https://www.academia.edu/77832138/Microscopic_Image_Analysis_Method_for_Identification_of_Indian_Herbal_Plants","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="77832137"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/77832137/A_robust_two_stage_super_resolution_algorithm"><img alt="Research paper thumbnail of A robust two-stage super-resolution algorithm" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/77832137/A_robust_two_stage_super_resolution_algorithm">A robust two-stage super-resolution algorithm</a></div><div class="wp-workCard_item"><span>2012 Nirma University International Conference on Engineering (NUiCONE)</span><span>, 2012</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT Super-Resolution is the process of constructing a high resolution image when a set of on...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT Super-Resolution is the process of constructing a high resolution image when a set of one or more low resolution input images is given. Traditionally, there are two methods exploited widely for enhancing the image via Super-Resolution viz. Single-Frame or Single-Based approach and Multi-Frame or Sequence-Based approach. Because the low resolution images have less information because of lower pixel density than their high resolution counterparts, the enhancement process requires missing image data to be calculated. In this paper, we have proposed a novel method that exploits the advantages of both these traditional methods. In the first phase, we improve a set of low resolution images via learning dictionary single frame method and in second phase we combine these by projecting these images onto convex sets thereby enhancing the image by information procured from multiple images. Experimental results show that our method works considerably better than state-of-the art Super Resolution enhancement methods.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="77832137"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="77832137"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 77832137; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=77832137]").text(description); $(".js-view-count[data-work-id=77832137]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 77832137; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='77832137']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=77832137]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":77832137,"title":"A robust two-stage super-resolution algorithm","internal_url":"https://www.academia.edu/77832137/A_robust_two_stage_super_resolution_algorithm","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="72031131"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/72031131/Implementation_of_IoT_based_Waste_Segregation_and_Collection_System"><img alt="Research paper thumbnail of Implementation of IoT based Waste Segregation and Collection System" class="work-thumbnail" src="https://attachments.academia-assets.com/81126769/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/72031131/Implementation_of_IoT_based_Waste_Segregation_and_Collection_System">Implementation of IoT based Waste Segregation and Collection System</a></div><div class="wp-workCard_item"><span>International Journal of Electronics and Telecommunications</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Waste management is a challenging problem for most of the countries. The current waste segregatio...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Waste management is a challenging problem for most of the countries. The current waste segregation and the collection method are not efficient and cost-effective. In this paper, a prototype is presented for smart waste management. It is also capable of waste segregation at the ground level and providing real-time data to the administrator. Impact and cost analysis of the deployment of smartbin is also presented considering one ward of Ahmedabad Municipal Corporation. It is clear from that deployment of this smartbin will save about 40% of the current expenditure for that ward.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e43eff7726b652b073234a66d2b0a4a7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":81126769,"asset_id":72031131,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/81126769/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="72031131"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="72031131"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 72031131; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=72031131]").text(description); $(".js-view-count[data-work-id=72031131]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 72031131; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='72031131']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "e43eff7726b652b073234a66d2b0a4a7" } } $('.js-work-strip[data-work-id=72031131]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":72031131,"title":"Implementation of IoT based Waste Segregation and Collection System","internal_url":"https://www.academia.edu/72031131/Implementation_of_IoT_based_Waste_Segregation_and_Collection_System","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[{"id":81126769,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/81126769/thumbnails/1.jpg","file_name":"78.pdf","download_url":"https://www.academia.edu/attachments/81126769/download_file","bulk_download_file_name":"Implementation_of_IoT_based_Waste_Segreg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/81126769/78-libre.pdf?1645416384=\u0026response-content-disposition=attachment%3B+filename%3DImplementation_of_IoT_based_Waste_Segreg.pdf\u0026Expires=1739844847\u0026Signature=OcsdETPkBTQXmlk4p1dzhykPoM-lYJgftr~Pr3gH-7JE-xPyd0vqupCRjEG1cmyHrPWFkNzb9P4avehXLX~vr41h0kg3U6k7aQHCp~sHMou8fH1Q4s4XVzzkLmCCft98VQbVsDuDofaj7MFxXBRgg4u~GqNo9CL-9JIafWhdCOs-BFWWCPm4Ev3iG5PswG5DuMjLnISjnN43-9HCZC0uVm9pyScm0gDMJJD2lbkz3ZRPuAJd1mTC0I6C1h1lpUHJLqPV3dVFb5rN6pKfspAfvrxqDUcWb3dPABO0fJARoLmZE7RCliHcNPv1yR48yckJg8LFGyv-3TSmTppPKdWOkQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65599114"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65599114/Software_Tools_for_Global_Navigation_Satellite_System"><img alt="Research paper thumbnail of Software Tools for Global Navigation Satellite System" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65599114/Software_Tools_for_Global_Navigation_Satellite_System">Software Tools for Global Navigation Satellite System</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65599114"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65599114"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65599114; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65599114]").text(description); $(".js-view-count[data-work-id=65599114]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65599114; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65599114']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65599114]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65599114,"title":"Software Tools for Global Navigation Satellite System","internal_url":"https://www.academia.edu/65599114/Software_Tools_for_Global_Navigation_Satellite_System","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65599113"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65599113/Microscopic_Image_Analysis_for_Herbal_Plant_Classification"><img alt="Research paper thumbnail of Microscopic Image Analysis for Herbal Plant Classification" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65599113/Microscopic_Image_Analysis_for_Herbal_Plant_Classification">Microscopic Image Analysis for Herbal Plant Classification</a></div><div class="wp-workCard_item"><span>The International Journal on the Image</span><span>, 2020</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65599113"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65599113"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65599113; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65599113]").text(description); $(".js-view-count[data-work-id=65599113]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65599113; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65599113']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65599113]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65599113,"title":"Microscopic Image Analysis for Herbal Plant Classification","internal_url":"https://www.academia.edu/65599113/Microscopic_Image_Analysis_for_Herbal_Plant_Classification","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65599112"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65599112/Edge_Detection_of_Microscopic_Image"><img alt="Research paper thumbnail of Edge Detection of Microscopic Image" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65599112/Edge_Detection_of_Microscopic_Image">Edge Detection of Microscopic Image</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Edge detection of herbal plants is a set of mathematical methods which aim at identifying points ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Edge detection of herbal plants is a set of mathematical methods which aim at identifying points in a digital image at which the image brightness changes sharply and has discontinuities. They are defined as the set of curved line segments termed edges. Effective edge detection for microscopic image of herbal plant is proposed through this paper which compares the edge detected images and then performs further segmentation. Comparison between Sobel operator, Prewitt, Canny and Robert cross operators is performed. Our method after efficient edge detection performs Gabor filter and K-means clustering to procure a better image. It is then subjected to further segmentation. Experimental methods in our proposed algorithm show that our method achieves a better edge detection as compared to other edge detector operators. Our proposed algorithm provides the maximum PSNR value of 43.684 amongst the other commercial edge detection operators.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65599112"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65599112"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65599112; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65599112]").text(description); $(".js-view-count[data-work-id=65599112]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65599112; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65599112']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65599112]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65599112,"title":"Edge Detection of Microscopic Image","internal_url":"https://www.academia.edu/65599112/Edge_Detection_of_Microscopic_Image","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65596868"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65596868/Classification_of_Indian_Herbal_Plants_based_on_powder_microscopic_images_using_Transfer_Learning"><img alt="Research paper thumbnail of Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65596868/Classification_of_Indian_Herbal_Plants_based_on_powder_microscopic_images_using_Transfer_Learning">Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The objective of this paper is to proficiently classify the microscopic images of powder of India...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The objective of this paper is to proficiently classify the microscopic images of powder of Indian Herbal plants. Since they hold great importance in medicine industry and their identification is only done by experts for the powdered form, we have eluded the need for an expert by automating the process, yielding decent results. Although, attempts have been made to perform this task but the methodologies used do not provide the results with high accuracy. Inspired from the state-of-the-art deep learning techniques we have performed the classification by fine-tuning 4 pre-trained models provided by the Keras library which have provided with great results on ImageNet dataset. Out of the 4 models used, VGG16 provides the highest accuracy, Precision, Recall and F1 score but is the slowest to train. MobileNet is fastest but is mediocre in other parameters while Xception is 2nd fastest but with lowest accuracy and InceptionV3 with mediocre results.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65596868"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65596868"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65596868; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65596868]").text(description); $(".js-view-count[data-work-id=65596868]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65596868; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65596868']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65596868]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65596868,"title":"Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning","internal_url":"https://www.academia.edu/65596868/Classification_of_Indian_Herbal_Plants_based_on_powder_microscopic_images_using_Transfer_Learning","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="60385333"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/60385333/Prediction_of_COVID_19_Disease_with_Chest_X_Rays_Using_Convolutional_Neural_Network"><img alt="Research paper thumbnail of Prediction of COVID-19 Disease with Chest X-Rays Using Convolutional Neural Network" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/60385333/Prediction_of_COVID_19_Disease_with_Chest_X_Rays_Using_Convolutional_Neural_Network">Prediction of COVID-19 Disease with Chest X-Rays Using Convolutional Neural Network</a></div><div class="wp-workCard_item"><span>2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="60385333"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="60385333"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 60385333; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=60385333]").text(description); $(".js-view-count[data-work-id=60385333]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 60385333; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='60385333']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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</script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="12017091" id="papers"><div class="js-work-strip profile--work_container" data-work-id="122922701"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/122922701/Automated_Digitization_of_Student_s_Marks_from_the_Answer_Book_Images_Using_a_Lightweight_CNN_Model"><img alt="Research paper thumbnail of Automated Digitization of Student’s Marks from the Answer-Book Images Using a Lightweight CNN Model" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/122922701/Automated_Digitization_of_Student_s_Marks_from_the_Answer_Book_Images_Using_a_Lightweight_CNN_Model">Automated Digitization of Student’s Marks from the Answer-Book Images Using a Lightweight CNN Model</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://niruni.academia.edu/rutulpatel">rutul patel</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://nirmauni.academia.edu/BhupendraFataniya">Bhupendra Fataniya</a></span></div><div class="wp-workCard_item"><span>SN Computer Science</span><span>, 2024</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Preparing student’s digital marksheet using images of student answer-books is a potential applica...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Preparing student’s digital marksheet using images of student answer-books is a potential application in academic institutions. Segmenting assigned marks automatically from answer-book images is extremely challenging, and it also demands pre-processing before the recognition stage. In addition, recognizing handwritten digits is crucial due to different writing styles. Existing research admits the superior performance of deep learning-based models in handwritten digit recognition (HDR) applications for popular datasets. However, their implication on real-time data for an experimental setup needs much attention. This paper presents an experimental setup that uses student answer-book images to record students’ marks digitally. We proposed a lightweight convolutional neural network (CNN) model for HDR. We also introduced a contour-based segmentation process for automatically extracting student details from answer-book images. The obtained results show the state-of-the-art performance of our proposed CNN model for real-time images. Further, introducing additional pre-processing before recognition significantly enhances the accuracy of the HDR experimental setup.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="122922701"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122922701"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122922701; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=122922701]").text(description); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="92525308"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/92525308/Real_Time_Object_Detection_in_Microscopic_Image_of_Indian_Herbal_Plants_using_YOLOv5_on_Jetson_Nano"><img alt="Research paper thumbnail of Real-Time Object Detection in Microscopic Image of Indian Herbal Plants using YOLOv5 on Jetson Nano" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/92525308/Real_Time_Object_Detection_in_Microscopic_Image_of_Indian_Herbal_Plants_using_YOLOv5_on_Jetson_Nano">Real-Time Object Detection in Microscopic Image of Indian Herbal Plants using YOLOv5 on Jetson Nano</a></div><div class="wp-workCard_item"><span>2022 International Conference on Connected Systems &amp; Intelligence (CSI)</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="92525308"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="92525308"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 92525308; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=92525308]").text(description); $(".js-view-count[data-work-id=92525308]").attr('title', description).tooltip(); 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</script> <div class="js-work-strip profile--work_container" data-work-id="92525307"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/92525307/Shape_Features_based_classification_of_Herbal_Plants_from_its_Powder_using_Microscopic_Image"><img alt="Research paper thumbnail of Shape Features based classification of Herbal Plants from its Powder using Microscopic Image" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/92525307/Shape_Features_based_classification_of_Herbal_Plants_from_its_Powder_using_Microscopic_Image">Shape Features based classification of Herbal Plants from its Powder using Microscopic Image</a></div><div class="wp-workCard_item"><span>Journal of image processing & pattern recognition progress</span><span>, Sep 24, 2018</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="92525307"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="92525307"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 92525307; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=92525307]").text(description); $(".js-view-count[data-work-id=92525307]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 92525307; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='92525307']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=92525307]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":92525307,"title":"Shape Features based classification of Herbal Plants from its Powder using Microscopic Image","internal_url":"https://www.academia.edu/92525307/Shape_Features_based_classification_of_Herbal_Plants_from_its_Powder_using_Microscopic_Image","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="92525305"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/92525305/Innovations_in_evaluation_An_integral_part_of_outcome_based_education"><img alt="Research paper thumbnail of Innovations in evaluation: An integral part of outcome based education" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/92525305/Innovations_in_evaluation_An_integral_part_of_outcome_based_education">Innovations in evaluation: An integral part of outcome based education</a></div><div class="wp-workCard_item"><span>2015 5th Nirma University International Conference on Engineering (NUiCONE)</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Education in India in 21st century demands innovations in the evaluation methods with the emergen...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Education in India in 21st century demands innovations in the evaluation methods with the emergence of Outcome Based Education (OBE). Lots of Research is already done in innovations in teaching and learning methods, but very few literatures on the innovations in evaluations are available. The paper discusses various innovative methods for the evaluation of students. The pros and cones of traditional exam and the new methods are also discussed. A survey on the various method is carried out and the results of the same are also presented.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="92525305"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="92525305"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 92525305; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=92525305]").text(description); $(".js-view-count[data-work-id=92525305]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 92525305; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='92525305']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=92525305]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":92525305,"title":"Innovations in evaluation: An integral part of outcome based education","internal_url":"https://www.academia.edu/92525305/Innovations_in_evaluation_An_integral_part_of_outcome_based_education","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="77832138"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/77832138/Microscopic_Image_Analysis_Method_for_Identification_of_Indian_Herbal_Plants"><img alt="Research paper thumbnail of Microscopic Image Analysis Method for Identification of Indian Herbal Plants" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/77832138/Microscopic_Image_Analysis_Method_for_Identification_of_Indian_Herbal_Plants">Microscopic Image Analysis Method for Identification of Indian Herbal Plants</a></div><div class="wp-workCard_item"><span>2014 International Conference on Devices, Circuits and Communications (ICDCCom)</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Identification of medicinal plant from its powder is a common task performed in pharmaceutical la...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Identification of medicinal plant from its powder is a common task performed in pharmaceutical labs and industries. In this paper, we are proposed a identification using machine intelligence. The algorithm is designed for the microscopic images of plant powder and segment the specific object from these images. From the extracted image unique features are identified and using this we train our algorithm and classify the test images. We have prepared the image database at our pharmacy lab for two plants namely Licorice and Kurchi plant. The proposed algorithm is applied on the variety of fifty images and results are described using confusion matrix and ROC curves.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="77832138"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="77832138"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 77832138; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=77832138]").text(description); $(".js-view-count[data-work-id=77832138]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 77832138; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='77832138']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=77832138]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":77832138,"title":"Microscopic Image Analysis Method for Identification of Indian Herbal Plants","internal_url":"https://www.academia.edu/77832138/Microscopic_Image_Analysis_Method_for_Identification_of_Indian_Herbal_Plants","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="77832137"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/77832137/A_robust_two_stage_super_resolution_algorithm"><img alt="Research paper thumbnail of A robust two-stage super-resolution algorithm" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/77832137/A_robust_two_stage_super_resolution_algorithm">A robust two-stage super-resolution algorithm</a></div><div class="wp-workCard_item"><span>2012 Nirma University International Conference on Engineering (NUiCONE)</span><span>, 2012</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT Super-Resolution is the process of constructing a high resolution image when a set of on...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT Super-Resolution is the process of constructing a high resolution image when a set of one or more low resolution input images is given. Traditionally, there are two methods exploited widely for enhancing the image via Super-Resolution viz. Single-Frame or Single-Based approach and Multi-Frame or Sequence-Based approach. Because the low resolution images have less information because of lower pixel density than their high resolution counterparts, the enhancement process requires missing image data to be calculated. In this paper, we have proposed a novel method that exploits the advantages of both these traditional methods. In the first phase, we improve a set of low resolution images via learning dictionary single frame method and in second phase we combine these by projecting these images onto convex sets thereby enhancing the image by information procured from multiple images. Experimental results show that our method works considerably better than state-of-the art Super Resolution enhancement methods.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="77832137"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="77832137"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 77832137; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=77832137]").text(description); $(".js-view-count[data-work-id=77832137]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 77832137; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='77832137']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=77832137]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":77832137,"title":"A robust two-stage super-resolution algorithm","internal_url":"https://www.academia.edu/77832137/A_robust_two_stage_super_resolution_algorithm","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="72031131"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/72031131/Implementation_of_IoT_based_Waste_Segregation_and_Collection_System"><img alt="Research paper thumbnail of Implementation of IoT based Waste Segregation and Collection System" class="work-thumbnail" src="https://attachments.academia-assets.com/81126769/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/72031131/Implementation_of_IoT_based_Waste_Segregation_and_Collection_System">Implementation of IoT based Waste Segregation and Collection System</a></div><div class="wp-workCard_item"><span>International Journal of Electronics and Telecommunications</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Waste management is a challenging problem for most of the countries. The current waste segregatio...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Waste management is a challenging problem for most of the countries. The current waste segregation and the collection method are not efficient and cost-effective. In this paper, a prototype is presented for smart waste management. It is also capable of waste segregation at the ground level and providing real-time data to the administrator. Impact and cost analysis of the deployment of smartbin is also presented considering one ward of Ahmedabad Municipal Corporation. It is clear from that deployment of this smartbin will save about 40% of the current expenditure for that ward.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e43eff7726b652b073234a66d2b0a4a7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":81126769,"asset_id":72031131,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/81126769/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="72031131"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="72031131"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 72031131; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=72031131]").text(description); $(".js-view-count[data-work-id=72031131]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 72031131; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='72031131']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "e43eff7726b652b073234a66d2b0a4a7" } } $('.js-work-strip[data-work-id=72031131]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":72031131,"title":"Implementation of IoT based Waste Segregation and Collection System","internal_url":"https://www.academia.edu/72031131/Implementation_of_IoT_based_Waste_Segregation_and_Collection_System","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[{"id":81126769,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/81126769/thumbnails/1.jpg","file_name":"78.pdf","download_url":"https://www.academia.edu/attachments/81126769/download_file","bulk_download_file_name":"Implementation_of_IoT_based_Waste_Segreg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/81126769/78-libre.pdf?1645416384=\u0026response-content-disposition=attachment%3B+filename%3DImplementation_of_IoT_based_Waste_Segreg.pdf\u0026Expires=1739844847\u0026Signature=OcsdETPkBTQXmlk4p1dzhykPoM-lYJgftr~Pr3gH-7JE-xPyd0vqupCRjEG1cmyHrPWFkNzb9P4avehXLX~vr41h0kg3U6k7aQHCp~sHMou8fH1Q4s4XVzzkLmCCft98VQbVsDuDofaj7MFxXBRgg4u~GqNo9CL-9JIafWhdCOs-BFWWCPm4Ev3iG5PswG5DuMjLnISjnN43-9HCZC0uVm9pyScm0gDMJJD2lbkz3ZRPuAJd1mTC0I6C1h1lpUHJLqPV3dVFb5rN6pKfspAfvrxqDUcWb3dPABO0fJARoLmZE7RCliHcNPv1yR48yckJg8LFGyv-3TSmTppPKdWOkQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65599114"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65599114/Software_Tools_for_Global_Navigation_Satellite_System"><img alt="Research paper thumbnail of Software Tools for Global Navigation Satellite System" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65599114/Software_Tools_for_Global_Navigation_Satellite_System">Software Tools for Global Navigation Satellite System</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65599114"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65599114"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65599114; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65599114]").text(description); $(".js-view-count[data-work-id=65599114]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65599114; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65599114']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65599114]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65599114,"title":"Software Tools for Global Navigation Satellite System","internal_url":"https://www.academia.edu/65599114/Software_Tools_for_Global_Navigation_Satellite_System","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65599113"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65599113/Microscopic_Image_Analysis_for_Herbal_Plant_Classification"><img alt="Research paper thumbnail of Microscopic Image Analysis for Herbal Plant Classification" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65599113/Microscopic_Image_Analysis_for_Herbal_Plant_Classification">Microscopic Image Analysis for Herbal Plant Classification</a></div><div class="wp-workCard_item"><span>The International Journal on the Image</span><span>, 2020</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65599113"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65599113"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65599113; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65599113]").text(description); $(".js-view-count[data-work-id=65599113]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65599113; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65599113']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65599113]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65599113,"title":"Microscopic Image Analysis for Herbal Plant Classification","internal_url":"https://www.academia.edu/65599113/Microscopic_Image_Analysis_for_Herbal_Plant_Classification","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65599112"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65599112/Edge_Detection_of_Microscopic_Image"><img alt="Research paper thumbnail of Edge Detection of Microscopic Image" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65599112/Edge_Detection_of_Microscopic_Image">Edge Detection of Microscopic Image</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Edge detection of herbal plants is a set of mathematical methods which aim at identifying points ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Edge detection of herbal plants is a set of mathematical methods which aim at identifying points in a digital image at which the image brightness changes sharply and has discontinuities. They are defined as the set of curved line segments termed edges. Effective edge detection for microscopic image of herbal plant is proposed through this paper which compares the edge detected images and then performs further segmentation. Comparison between Sobel operator, Prewitt, Canny and Robert cross operators is performed. Our method after efficient edge detection performs Gabor filter and K-means clustering to procure a better image. It is then subjected to further segmentation. Experimental methods in our proposed algorithm show that our method achieves a better edge detection as compared to other edge detector operators. Our proposed algorithm provides the maximum PSNR value of 43.684 amongst the other commercial edge detection operators.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65599112"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65599112"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65599112; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65599112]").text(description); $(".js-view-count[data-work-id=65599112]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65599112; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65599112']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65599112]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65599112,"title":"Edge Detection of Microscopic Image","internal_url":"https://www.academia.edu/65599112/Edge_Detection_of_Microscopic_Image","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="65596868"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/65596868/Classification_of_Indian_Herbal_Plants_based_on_powder_microscopic_images_using_Transfer_Learning"><img alt="Research paper thumbnail of Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/65596868/Classification_of_Indian_Herbal_Plants_based_on_powder_microscopic_images_using_Transfer_Learning">Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The objective of this paper is to proficiently classify the microscopic images of powder of India...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The objective of this paper is to proficiently classify the microscopic images of powder of Indian Herbal plants. Since they hold great importance in medicine industry and their identification is only done by experts for the powdered form, we have eluded the need for an expert by automating the process, yielding decent results. Although, attempts have been made to perform this task but the methodologies used do not provide the results with high accuracy. Inspired from the state-of-the-art deep learning techniques we have performed the classification by fine-tuning 4 pre-trained models provided by the Keras library which have provided with great results on ImageNet dataset. Out of the 4 models used, VGG16 provides the highest accuracy, Precision, Recall and F1 score but is the slowest to train. MobileNet is fastest but is mediocre in other parameters while Xception is 2nd fastest but with lowest accuracy and InceptionV3 with mediocre results.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="65596868"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="65596868"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 65596868; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=65596868]").text(description); $(".js-view-count[data-work-id=65596868]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 65596868; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='65596868']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=65596868]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":65596868,"title":"Classification of Indian Herbal Plants based on powder microscopic images using Transfer Learning","internal_url":"https://www.academia.edu/65596868/Classification_of_Indian_Herbal_Plants_based_on_powder_microscopic_images_using_Transfer_Learning","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="60385333"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/60385333/Prediction_of_COVID_19_Disease_with_Chest_X_Rays_Using_Convolutional_Neural_Network"><img alt="Research paper thumbnail of Prediction of COVID-19 Disease with Chest X-Rays Using Convolutional Neural Network" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/60385333/Prediction_of_COVID_19_Disease_with_Chest_X_Rays_Using_Convolutional_Neural_Network">Prediction of COVID-19 Disease with Chest X-Rays Using Convolutional Neural Network</a></div><div class="wp-workCard_item"><span>2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="60385333"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="60385333"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 60385333; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=60385333]").text(description); $(".js-view-count[data-work-id=60385333]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 60385333; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='60385333']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=60385333]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":60385333,"title":"Prediction of COVID-19 Disease with Chest X-Rays Using Convolutional Neural Network","internal_url":"https://www.academia.edu/60385333/Prediction_of_COVID_19_Disease_with_Chest_X_Rays_Using_Convolutional_Neural_Network","owner_id":9104583,"coauthors_can_edit":true,"owner":{"id":9104583,"first_name":"Bhupendra","middle_initials":null,"last_name":"Fataniya","page_name":"BhupendraFataniya","domain_name":"nirmauni","created_at":"2014-02-12T20:16:28.833-08:00","display_name":"Bhupendra Fataniya","url":"https://nirmauni.academia.edu/BhupendraFataniya"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="53855764"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/53855764/Herbal_Plant_Classification_Using_Rotational_and_Scale_Invariant_Shape_Based_Features"><img alt="Research paper thumbnail of Herbal Plant Classification Using Rotational and Scale Invariant Shape Based Features" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/53855764/Herbal_Plant_Classification_Using_Rotational_and_Scale_Invariant_Shape_Based_Features">Herbal Plant Classification Using Rotational and Scale Invariant Shape Based Features</a></div><div class="wp-workCard_item"><span>Sensor Letters</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="53855764"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="53855764"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 53855764; 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