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{"id":52099409,"title":"Resemblance of Biological Particle Swarm Optimization and Particle Swarm Optimization for CBFR by using NN","internal_url":"https://www.academia.edu/52099409/Resemblance_of_Biological_Particle_Swarm_Optimization_and_Particle_Swarm_Optimization_for_CBFR_by_using_NN","owner_id":5285891,"coauthors_can_edit":true,"owner":{"id":5285891,"first_name":"Deepika","middle_initials":null,"last_name":"Dubey","page_name":"DubeyDeepika","domain_name":"independent","created_at":"2013-08-26T16:17:32.047-07:00","display_name":"Deepika Dubey","url":"https://independent.academia.edu/DubeyDeepika"},"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="52099408"><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/52099408/Echelon_Based_Pose_Generalization_of_Facial_Images_Approaches"><img alt="Research paper thumbnail of Echelon Based Pose Generalization of Facial Images Approaches" class="work-thumbnail" src="https://attachments.academia-assets.com/69520131/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/52099408/Echelon_Based_Pose_Generalization_of_Facial_Images_Approaches">Echelon Based Pose Generalization of Facial Images Approaches</a></div><div class="wp-workCard_item"><span>Asia-pacific Journal of Convergent Research Interchange</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Face recognition having many applications applied different in security, using in access control,...</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">Face recognition having many applications applied different in security, using in access control, applied on gaming, also effect by aging effect, health issues, and internet communication and so on. It has been perform on different images either they are stored in database or a new image is captured and take it as input image. Face recognition algorithms having different fields of application. The intelligent image (face) recognition system consists of various components through which human identification and recognition has been done. In real world practical applications unconstrained conditions like illumination and create variations, occlusion and expressions are to be faced by the users. in this paper discuss about the pose invariant technology also study the challenges during face recognition under unconstrained conditions like illumination and cause variations, basically it proposes several possible pose invariant technologies future directions which is excluded from the challenges used.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="34494795bc26942fcba16747b81d25e6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520131,"asset_id":52099408,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520131/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="52099408"><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="52099408"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099408; 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In this paper,...</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">Three-dimensional (3D) face models can handle large pose face recognition problem. In this paper, we propose survey on pose-invariant face recognition method. By scrutinizing study depth, here we only analysis on pose invariant technique in face recognition method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images of the face in the database can be the same view as the probe during surveillance. In this survey of face detection technology has been presented in this work feature based approach with low level analysis has been done. Information, color, shape, model etc. has been considered for investigation. The technique considered here also explained in other papers. Depth information has improved the performance of face recognition with large pose variations up to the mark able angle and under even more challenging conditions.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f1e1650f75d1ae40ed3123f16a7702d7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520132,"asset_id":52099406,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520132/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="52099406"><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="52099406"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099406; 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=52099402]").text(description); $(".js-view-count[data-work-id=52099402]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 52099402; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='52099402']"); 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" } } $('.js-work-strip[data-work-id=52099402]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52099402,"title":"Surevey on Digital Watermarking Techniques","internal_url":"https://www.academia.edu/52099402/Surevey_on_Digital_Watermarking_Techniques","owner_id":5285891,"coauthors_can_edit":true,"owner":{"id":5285891,"first_name":"Deepika","middle_initials":null,"last_name":"Dubey","page_name":"DubeyDeepika","domain_name":"independent","created_at":"2013-08-26T16:17:32.047-07:00","display_name":"Deepika Dubey","url":"https://independent.academia.edu/DubeyDeepika"},"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="52099401"><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/52099401/A_Review_on_Different_Digital_Watermarking_Techniques"><img alt="Research paper thumbnail of A Review on Different Digital Watermarking Techniques" class="work-thumbnail" src="https://attachments.academia-assets.com/69520130/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/52099401/A_Review_on_Different_Digital_Watermarking_Techniques">A Review on Different Digital Watermarking Techniques</a></div><div class="wp-workCard_item"><span>International Journal of Signal Processing, Image Processing and Pattern Recognition</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A digital watermark is a type of indicator covertly embedded in the noise tolerant signal such as...</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">A digital watermark is a type of indicator covertly embedded in the noise tolerant signal such as an image or audio data. Digital watermarking is the method that embeds information known as a watermark into the multimedia object such that the watermark can be extracted or detected later to create an assertion about the object. Embedded watermark will permit recognizing the owner of the work hardware implementation. This idea is applicable for the digital video and audio also. Embedding a digital signal (image, video or video) with data which cannot be easily eliminated is called digital watermarking. Digital watermarks may be used to the authenticate the integrity or authenticity of the carrier signal or to display the identity of its owners Digital watermarking is used as a key result to create the document transferring protected from unlawful interferences. Digital watermark methods are used in numerous areas such as copyright owner identification, protection and broadcast monitoring. Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image, which is overlaid on the host image, and provides a means of protecting the image. In this paper, aim is to present a survey of numerous methods on the basis of digital image watermarking. The digital watermarking method is becoming more important in this developing society of internet. The goal of this implementation is to survey the different techniques for Digital Watermarking.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cc6bf54e84aa247a17fdd3bb0715fb25" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520130,"asset_id":52099401,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520130/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="52099401"><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="52099401"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099401; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=52099401]").text(description); $(".js-view-count[data-work-id=52099401]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 52099401; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='52099401']"); 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: "cc6bf54e84aa247a17fdd3bb0715fb25" } } $('.js-work-strip[data-work-id=52099401]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52099401,"title":"A Review on Different Digital Watermarking Techniques","internal_url":"https://www.academia.edu/52099401/A_Review_on_Different_Digital_Watermarking_Techniques","owner_id":5285891,"coauthors_can_edit":true,"owner":{"id":5285891,"first_name":"Deepika","middle_initials":null,"last_name":"Dubey","page_name":"DubeyDeepika","domain_name":"independent","created_at":"2013-08-26T16:17:32.047-07:00","display_name":"Deepika Dubey","url":"https://independent.academia.edu/DubeyDeepika"},"attachments":[{"id":69520130,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69520130/thumbnails/1.jpg","file_name":"ijsip.2015.8.10.pdf","download_url":"https://www.academia.edu/attachments/69520130/download_file","bulk_download_file_name":"A_Review_on_Different_Digital_Watermarki.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69520130/ijsip.2015.8.10-libre.pdf?1631726315=\u0026response-content-disposition=attachment%3B+filename%3DA_Review_on_Different_Digital_Watermarki.pdf\u0026Expires=1740271075\u0026Signature=Y9Pa689jVwyf1xHKtcvbwpGDcRPwkDLBXEwLoiwCPyKrXGrfHoaHbo9ZySajEoXH68P1~2Fw3JRdU6glwj~OHslk5CHi5O-SCbmmcoN62sYoW5NqHwoaE9WXNCmq~tKh09H49yrEtxuhtFocGtDCL2EQOE4JgFJpzEesgXjnYT2HMpHM2fmoIIS6QXNzRUmrx6UoXM2YIkAjyupqXSzmLf1nXjZaZF7gtpriGy-t4fxlt-j07w8JV3WJhANriptrV-dXudcNNd532-Lt-XozrbbGr9dC4rYOaoj7f8oNDyqCEiFXi~T~6i-8ynDv004QBQnbQgq7cDuT-hj19OxGVA__\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="52099400"><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/52099400/A_Survey_Of_Digital_Image_Tampering_Techniques"><img alt="Research paper thumbnail of A Survey Of Digital Image Tampering Techniques" class="work-thumbnail" src="https://attachments.academia-assets.com/69520133/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/52099400/A_Survey_Of_Digital_Image_Tampering_Techniques">A Survey Of Digital Image Tampering Techniques</a></div><div class="wp-workCard_item"><span>International Journal of Signal Processing, Image Processing and Pattern Recognition</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Due to powerful computers and advanced photo-editing software tools the manipulation of images ha...</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">Due to powerful computers and advanced photo-editing software tools the manipulation of images has become an easy task. Confirming the authenticity of images and detecting tampered regions in an image without any knowledge about the image content is an important part of the research field. An effort is made to survey the recent advancements being made in the field of digital image forgery detection and thus passive methods for forgery detection are being presented. Blind or passive methods do not require any explicit former information about the image. In the first part, various image forgery detection techniques are classified and then an overview of passive image authentication is presented and the existing blind forgery detection techniques are reviewed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a7bf3e091b1e22d7f4a291c9c886c623" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520133,"asset_id":52099400,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520133/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="52099400"><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="52099400"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099400; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="52099399"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/52099399/Reducing_Forged_Features_Using_Tampered_and_Inconsistent_Image_Detection_Techniques_in_Digital_Image_Processing"><img alt="Research paper thumbnail of Reducing Forged Features Using Tampered and Inconsistent Image Detection Techniques in Digital Image Processing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/52099399/Reducing_Forged_Features_Using_Tampered_and_Inconsistent_Image_Detection_Techniques_in_Digital_Image_Processing">Reducing Forged Features Using Tampered and Inconsistent Image Detection Techniques in Digital Image Processing</a></div><div class="wp-workCard_item"><span>2015 Fifth International Conference on Communication Systems and Network Technologies</span><span>, 2015</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="52099399"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="52099399"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099399; 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</script> <div class="js-work-strip profile--work_container" data-work-id="52097641"><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/52097641/Optimize_Prototype_Classification_Based_on_GA_ANT_Hybrid_Technique"><img alt="Research paper thumbnail of Optimize Prototype Classification Based on GA ANT Hybrid Technique" class="work-thumbnail" src="https://attachments.academia-assets.com/69519187/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/52097641/Optimize_Prototype_Classification_Based_on_GA_ANT_Hybrid_Technique">Optimize Prototype Classification Based on GA ANT Hybrid Technique</a></div><div class="wp-workCard_item"><span>2013 5th International Conference on Computational Intelligence and Communication Networks</span><span>, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Learning is the process of generating useful information from a huge volume of data. Learning can...</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">Learning is the process of generating useful information from a huge volume of data. Learning can be classified as supervised learning and unsupervised learning. Classification is a kind of supervised learning and Clustering is a kind of unsupervised learning. Prototype clustering and classification is new technique in data mining. The prototype clustering and classification also called as ensemble clustering and classification. The Proposed novel method for prototype clustering and classification based on ant colony optimization and geneticalgorithm. We conduct experiments with the prototype clustering and classification based on GA ANT hybrid technique using UCI repository with three data sets. The experimental results show that the proposed approach can achieve superior classification performance than other commonly used data mining approaches.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="22028edab0f3b877e046a77e6d731689" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69519187,"asset_id":52097641,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69519187/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="52097641"><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="52097641"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52097641; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="11757803" id="papers"><div class="js-work-strip profile--work_container" data-work-id="52099409"><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/52099409/Resemblance_of_Biological_Particle_Swarm_Optimization_and_Particle_Swarm_Optimization_for_CBFR_by_using_NN"><img alt="Research paper thumbnail of Resemblance of Biological Particle Swarm Optimization and Particle Swarm Optimization for CBFR by using NN" 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/52099409/Resemblance_of_Biological_Particle_Swarm_Optimization_and_Particle_Swarm_Optimization_for_CBFR_by_using_NN">Resemblance of Biological Particle Swarm Optimization and Particle Swarm Optimization for CBFR by using NN</a></div><div class="wp-workCard_item"><span>Materials Today: Proceedings</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="52099409"><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="52099409"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099409; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=52099409]").text(description); $(".js-view-count[data-work-id=52099409]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 52099409; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='52099409']"); 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 class="js-work-strip profile--work_container" data-work-id="52099408"><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/52099408/Echelon_Based_Pose_Generalization_of_Facial_Images_Approaches"><img alt="Research paper thumbnail of Echelon Based Pose Generalization of Facial Images Approaches" class="work-thumbnail" src="https://attachments.academia-assets.com/69520131/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/52099408/Echelon_Based_Pose_Generalization_of_Facial_Images_Approaches">Echelon Based Pose Generalization of Facial Images Approaches</a></div><div class="wp-workCard_item"><span>Asia-pacific Journal of Convergent Research Interchange</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Face recognition having many applications applied different in security, using in access control,...</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">Face recognition having many applications applied different in security, using in access control, applied on gaming, also effect by aging effect, health issues, and internet communication and so on. It has been perform on different images either they are stored in database or a new image is captured and take it as input image. Face recognition algorithms having different fields of application. The intelligent image (face) recognition system consists of various components through which human identification and recognition has been done. In real world practical applications unconstrained conditions like illumination and create variations, occlusion and expressions are to be faced by the users. in this paper discuss about the pose invariant technology also study the challenges during face recognition under unconstrained conditions like illumination and cause variations, basically it proposes several possible pose invariant technologies future directions which is excluded from the challenges used.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="34494795bc26942fcba16747b81d25e6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520131,"asset_id":52099408,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520131/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="52099408"><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="52099408"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099408; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=52099407]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52099407,"title":"Interactive Biogeography Particle Swarm Optimization for Content Based Image Retrieval","internal_url":"https://www.academia.edu/52099407/Interactive_Biogeography_Particle_Swarm_Optimization_for_Content_Based_Image_Retrieval","owner_id":5285891,"coauthors_can_edit":true,"owner":{"id":5285891,"first_name":"Deepika","middle_initials":null,"last_name":"Dubey","page_name":"DubeyDeepika","domain_name":"independent","created_at":"2013-08-26T16:17:32.047-07:00","display_name":"Deepika Dubey","url":"https://independent.academia.edu/DubeyDeepika"},"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="52099406"><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/52099406/Scrutinize_Study_on_Face_Recognition_by_Pose_Invariant_Methodology"><img alt="Research paper thumbnail of Scrutinize Study on Face Recognition by Pose Invariant Methodology" class="work-thumbnail" src="https://attachments.academia-assets.com/69520132/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/52099406/Scrutinize_Study_on_Face_Recognition_by_Pose_Invariant_Methodology">Scrutinize Study on Face Recognition by Pose Invariant Methodology</a></div><div class="wp-workCard_item"><span>International Journal of Future Generation Communication and Networking</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Three-dimensional (3D) face models can handle large pose face recognition problem. In this paper,...</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">Three-dimensional (3D) face models can handle large pose face recognition problem. In this paper, we propose survey on pose-invariant face recognition method. By scrutinizing study depth, here we only analysis on pose invariant technique in face recognition method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images of the face in the database can be the same view as the probe during surveillance. In this survey of face detection technology has been presented in this work feature based approach with low level analysis has been done. Information, color, shape, model etc. has been considered for investigation. The technique considered here also explained in other papers. Depth information has improved the performance of face recognition with large pose variations up to the mark able angle and under even more challenging conditions.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f1e1650f75d1ae40ed3123f16a7702d7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520132,"asset_id":52099406,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520132/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="52099406"><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="52099406"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099406; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=52099403]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52099403,"title":"Improved Detection of 1-2-4 LSB Steganography and RSA Cryptography in Color and Grayscale Images","internal_url":"https://www.academia.edu/52099403/Improved_Detection_of_1_2_4_LSB_Steganography_and_RSA_Cryptography_in_Color_and_Grayscale_Images","owner_id":5285891,"coauthors_can_edit":true,"owner":{"id":5285891,"first_name":"Deepika","middle_initials":null,"last_name":"Dubey","page_name":"DubeyDeepika","domain_name":"independent","created_at":"2013-08-26T16:17:32.047-07:00","display_name":"Deepika Dubey","url":"https://independent.academia.edu/DubeyDeepika"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="52099402"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/52099402/Surevey_on_Digital_Watermarking_Techniques"><img alt="Research paper thumbnail of Surevey on Digital Watermarking Techniques" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/52099402/Surevey_on_Digital_Watermarking_Techniques">Surevey on Digital Watermarking Techniques</a></div><div class="wp-workCard_item"><span>International Journal of Signal Processing, Image Processing and Pattern Recognition</span><span>, 2016</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="52099402"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="52099402"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099402; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=52099402]").text(description); $(".js-view-count[data-work-id=52099402]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 52099402; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='52099402']"); 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" } } $('.js-work-strip[data-work-id=52099402]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52099402,"title":"Surevey on Digital Watermarking Techniques","internal_url":"https://www.academia.edu/52099402/Surevey_on_Digital_Watermarking_Techniques","owner_id":5285891,"coauthors_can_edit":true,"owner":{"id":5285891,"first_name":"Deepika","middle_initials":null,"last_name":"Dubey","page_name":"DubeyDeepika","domain_name":"independent","created_at":"2013-08-26T16:17:32.047-07:00","display_name":"Deepika Dubey","url":"https://independent.academia.edu/DubeyDeepika"},"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="52099401"><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/52099401/A_Review_on_Different_Digital_Watermarking_Techniques"><img alt="Research paper thumbnail of A Review on Different Digital Watermarking Techniques" class="work-thumbnail" src="https://attachments.academia-assets.com/69520130/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/52099401/A_Review_on_Different_Digital_Watermarking_Techniques">A Review on Different Digital Watermarking Techniques</a></div><div class="wp-workCard_item"><span>International Journal of Signal Processing, Image Processing and Pattern Recognition</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A digital watermark is a type of indicator covertly embedded in the noise tolerant signal such as...</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">A digital watermark is a type of indicator covertly embedded in the noise tolerant signal such as an image or audio data. Digital watermarking is the method that embeds information known as a watermark into the multimedia object such that the watermark can be extracted or detected later to create an assertion about the object. Embedded watermark will permit recognizing the owner of the work hardware implementation. This idea is applicable for the digital video and audio also. Embedding a digital signal (image, video or video) with data which cannot be easily eliminated is called digital watermarking. Digital watermarks may be used to the authenticate the integrity or authenticity of the carrier signal or to display the identity of its owners Digital watermarking is used as a key result to create the document transferring protected from unlawful interferences. Digital watermark methods are used in numerous areas such as copyright owner identification, protection and broadcast monitoring. Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image, which is overlaid on the host image, and provides a means of protecting the image. In this paper, aim is to present a survey of numerous methods on the basis of digital image watermarking. The digital watermarking method is becoming more important in this developing society of internet. The goal of this implementation is to survey the different techniques for Digital Watermarking.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cc6bf54e84aa247a17fdd3bb0715fb25" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520130,"asset_id":52099401,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520130/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="52099401"><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="52099401"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099401; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=52099401]").text(description); $(".js-view-count[data-work-id=52099401]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 52099401; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='52099401']"); 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: "cc6bf54e84aa247a17fdd3bb0715fb25" } } $('.js-work-strip[data-work-id=52099401]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52099401,"title":"A Review on Different Digital Watermarking Techniques","internal_url":"https://www.academia.edu/52099401/A_Review_on_Different_Digital_Watermarking_Techniques","owner_id":5285891,"coauthors_can_edit":true,"owner":{"id":5285891,"first_name":"Deepika","middle_initials":null,"last_name":"Dubey","page_name":"DubeyDeepika","domain_name":"independent","created_at":"2013-08-26T16:17:32.047-07:00","display_name":"Deepika Dubey","url":"https://independent.academia.edu/DubeyDeepika"},"attachments":[{"id":69520130,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69520130/thumbnails/1.jpg","file_name":"ijsip.2015.8.10.pdf","download_url":"https://www.academia.edu/attachments/69520130/download_file","bulk_download_file_name":"A_Review_on_Different_Digital_Watermarki.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69520130/ijsip.2015.8.10-libre.pdf?1631726315=\u0026response-content-disposition=attachment%3B+filename%3DA_Review_on_Different_Digital_Watermarki.pdf\u0026Expires=1740271075\u0026Signature=Y9Pa689jVwyf1xHKtcvbwpGDcRPwkDLBXEwLoiwCPyKrXGrfHoaHbo9ZySajEoXH68P1~2Fw3JRdU6glwj~OHslk5CHi5O-SCbmmcoN62sYoW5NqHwoaE9WXNCmq~tKh09H49yrEtxuhtFocGtDCL2EQOE4JgFJpzEesgXjnYT2HMpHM2fmoIIS6QXNzRUmrx6UoXM2YIkAjyupqXSzmLf1nXjZaZF7gtpriGy-t4fxlt-j07w8JV3WJhANriptrV-dXudcNNd532-Lt-XozrbbGr9dC4rYOaoj7f8oNDyqCEiFXi~T~6i-8ynDv004QBQnbQgq7cDuT-hj19OxGVA__\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="52099400"><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/52099400/A_Survey_Of_Digital_Image_Tampering_Techniques"><img alt="Research paper thumbnail of A Survey Of Digital Image Tampering Techniques" class="work-thumbnail" src="https://attachments.academia-assets.com/69520133/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/52099400/A_Survey_Of_Digital_Image_Tampering_Techniques">A Survey Of Digital Image Tampering Techniques</a></div><div class="wp-workCard_item"><span>International Journal of Signal Processing, Image Processing and Pattern Recognition</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Due to powerful computers and advanced photo-editing software tools the manipulation of images ha...</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">Due to powerful computers and advanced photo-editing software tools the manipulation of images has become an easy task. Confirming the authenticity of images and detecting tampered regions in an image without any knowledge about the image content is an important part of the research field. An effort is made to survey the recent advancements being made in the field of digital image forgery detection and thus passive methods for forgery detection are being presented. Blind or passive methods do not require any explicit former information about the image. In the first part, various image forgery detection techniques are classified and then an overview of passive image authentication is presented and the existing blind forgery detection techniques are reviewed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a7bf3e091b1e22d7f4a291c9c886c623" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69520133,"asset_id":52099400,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69520133/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="52099400"><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="52099400"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099400; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="52099399"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/52099399/Reducing_Forged_Features_Using_Tampered_and_Inconsistent_Image_Detection_Techniques_in_Digital_Image_Processing"><img alt="Research paper thumbnail of Reducing Forged Features Using Tampered and Inconsistent Image Detection Techniques in Digital Image Processing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/52099399/Reducing_Forged_Features_Using_Tampered_and_Inconsistent_Image_Detection_Techniques_in_Digital_Image_Processing">Reducing Forged Features Using Tampered and Inconsistent Image Detection Techniques in Digital Image Processing</a></div><div class="wp-workCard_item"><span>2015 Fifth International Conference on Communication Systems and Network Technologies</span><span>, 2015</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="52099399"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="52099399"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52099399; 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</script> <div class="js-work-strip profile--work_container" data-work-id="52097641"><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/52097641/Optimize_Prototype_Classification_Based_on_GA_ANT_Hybrid_Technique"><img alt="Research paper thumbnail of Optimize Prototype Classification Based on GA ANT Hybrid Technique" class="work-thumbnail" src="https://attachments.academia-assets.com/69519187/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/52097641/Optimize_Prototype_Classification_Based_on_GA_ANT_Hybrid_Technique">Optimize Prototype Classification Based on GA ANT Hybrid Technique</a></div><div class="wp-workCard_item"><span>2013 5th International Conference on Computational Intelligence and Communication Networks</span><span>, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Learning is the process of generating useful information from a huge volume of data. Learning can...</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">Learning is the process of generating useful information from a huge volume of data. Learning can be classified as supervised learning and unsupervised learning. Classification is a kind of supervised learning and Clustering is a kind of unsupervised learning. Prototype clustering and classification is new technique in data mining. The prototype clustering and classification also called as ensemble clustering and classification. The Proposed novel method for prototype clustering and classification based on ant colony optimization and geneticalgorithm. We conduct experiments with the prototype clustering and classification based on GA ANT hybrid technique using UCI repository with three data sets. The experimental results show that the proposed approach can achieve superior classification performance than other commonly used data mining approaches.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="22028edab0f3b877e046a77e6d731689" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69519187,"asset_id":52097641,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69519187/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="52097641"><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="52097641"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52097641; 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