CINXE.COM

<!DOCTYPE html> <html > <head> <meta charset="utf-8"> <meta rel="search" type="application/opensearchdescription+xml" href="/open_search.xml" title="Academia.edu"> <meta content="width=device-width, initial-scale=1" name="viewport"> <meta name="google-site-verification" content="bKJMBZA7E43xhDOopFZkssMMkBRjvYERV-NaN4R6mrs"> <meta name="csrf-param" content="authenticity_token" /> <meta name="csrf-token" content="B4T930KhBmJIMxX84zc4aJ85YpTThpomM06DL9h2lLsQj+D2uYhPjpzQdozQOPBsYoIjraUzX/WC8jfZb1liUw==" /> <meta name="citation_title" content="VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH" /> <meta name="citation_publication_date" content="2021/01/01" /> <meta name="citation_journal_title" content="Scientific Journal of Silesian University of Technology. Series Transport " /> <meta name="citation_author" content="Mandalapu Sarada Devi" /> <meta name="citation_author" content="JANAK TRIVEDI" /> <meta name="twitter:card" content="summary" /> <meta name="twitter:url" content="https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH" /> <meta name="twitter:title" content="VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH" /> <meta name="twitter:description" content="We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System" /> <meta name="twitter:image" content="https://0.academia-photos.com/52647603/40130788/32972826/s200_janak.trivedi.jpg" /> <meta property="fb:app_id" content="2369844204" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH" /> <meta property="og:title" content="VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH" /> <meta property="og:image" content="http://a.academia-assets.com/images/open-graph-icons/fb-paper.gif" /> <meta property="og:description" content="We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System" /> <meta property="article:author" content="https://gtu-in.academia.edu/JANAKTRIVEDI" /> <meta property="article:author" content="https://independent.academia.edu/MandalapuSaradaDevi" /> <meta name="description" content="We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System" /> <title>(PDF) VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH | JANAK TRIVEDI and Mandalapu Sarada Devi - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '49879c2402910372f4abc62630a427bbe033d190'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1732499851000); window.Aedu.timeDifference = new Date().getTime() - 1732499851000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System (ITS) to build a smart city. In this article, three different vehicles: bike, car and truck classification are considered for around 3,000 bikes, 6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract different vehicle dataset\u0026amp;#39;s different features without a manual selection of features. The accuracy of CNN is measured in terms of the confidence values of the detected object. The highest confidence value is about 0.99 in the case of the bike category vehicle classification. The automatic vehicle classification supports building an electronic toll collection system and identifying emergency vehicles in the traffic.","author":[{"@context":"https://schema.org","@type":"Person","name":"JANAK TRIVEDI"},{"@context":"https://schema.org","@type":"Person","name":"Mandalapu Sarada Devi"}],"contributor":[{"@context":"https://schema.org","@type":"Person","name":"Mandalapu Sarada Devi"}],"dateCreated":"2021-07-16","dateModified":"2021-11-11","datePublished":"2021-01-01","headline":"VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH","inLanguage":"en","keywords":["Computer Science","Artificial Intelligence","Computer Vision","Image Processing","Machine Learning","Real Time Computing","Electronics \u0026 Telecommunication Engineering","Digital Signal Processing","Intelligent Transportation Systems","Video Processing","Automotive","Deep Learning","Image and Video Processing","Tracking Vehicles in Real Time","Real-Time Analysis","Trucks","Vehicle Classification","Electronics and Communications Engineering","Car Image Classification"],"locationCreated":null,"publication":"Scientific Journal of Silesian University of Technology. Series Transport","publisher":{"@context":"https://schema.org","@type":"Organization","name":null},"image":null,"thumbnailUrl":null,"url":"https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH","sourceOrganization":[{"@context":"https://schema.org","@type":"EducationalOrganization","name":"gtu-in"},{"@context":"https://schema.org","@type":"EducationalOrganization","name":null}]}</script><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/single_work_page/loswp-352e32ba4e89304dc0b4fa5b3952eef2198174c54cdb79066bc62e91c68a1a91.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/body-8d679e925718b5e8e4b18e9a4fab37f7eaa99e43386459376559080ac8f2856a.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/button-3cea6e0ad4715ed965c49bfb15dedfc632787b32ff6d8c3a474182b231146ab7.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/text_button-73590134e40cdb49f9abdc8e796cc00dc362693f3f0f6137d6cf9bb78c318ce7.css" /><link crossorigin="" href="https://fonts.gstatic.com/" rel="preconnect" /><link href="https://fonts.googleapis.com/css2?family=DM+Sans:ital,opsz,wght@0,9..40,100..1000;1,9..40,100..1000&family=Gupter:wght@400;500;700&family=IBM+Plex+Mono:wght@300;400&family=Material+Symbols+Outlined:opsz,wght,FILL,GRAD@20,400,0,0&display=swap" rel="stylesheet" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/common-10fa40af19d25203774df2d4a03b9b5771b45109c2304968038e88a81d1215c5.css" /> </head> <body> <div id='react-modal'></div> <div class="js-upgrade-ie-banner" style="display: none; text-align: center; padding: 8px 0; background-color: #ebe480;"><p style="color: #000; font-size: 12px; margin: 0 0 4px;">Academia.edu no longer supports Internet Explorer.</p><p style="color: #000; font-size: 12px; margin: 0;">To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to <a href="https://www.academia.edu/upgrade-browser">upgrade your browser</a>.</p></div><script>// Show this banner for all versions of IE if (!!window.MSInputMethodContext || /(MSIE)/.test(navigator.userAgent)) { document.querySelector('.js-upgrade-ie-banner').style.display = 'block'; }</script> <div class="bootstrap login"><div class="modal fade login-modal" id="login-modal"><div class="login-modal-dialog modal-dialog"><div class="modal-content"><div class="modal-header"><button class="close close" data-dismiss="modal" type="button"><span aria-hidden="true">×</span><span class="sr-only">Close</span></button><h4 class="modal-title text-center"><strong>Log In</strong></h4></div><div class="modal-body"><div class="row"><div class="col-xs-10 col-xs-offset-1"><button class="btn btn-fb btn-lg btn-block btn-v-center-content" id="login-facebook-oauth-button"><svg style="float: left; width: 19px; line-height: 1em; margin-right: .3em;" aria-hidden="true" focusable="false" data-prefix="fab" data-icon="facebook-square" class="svg-inline--fa fa-facebook-square fa-w-14" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><path fill="currentColor" d="M400 32H48A48 48 0 0 0 0 80v352a48 48 0 0 0 48 48h137.25V327.69h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.27c-30.81 0-40.42 19.12-40.42 38.73V256h68.78l-11 71.69h-57.78V480H400a48 48 0 0 0 48-48V80a48 48 0 0 0-48-48z"></path></svg><small><strong>Log in</strong> with <strong>Facebook</strong></small></button><br /><button class="btn btn-google btn-lg btn-block btn-v-center-content" id="login-google-oauth-button"><svg style="float: left; width: 22px; line-height: 1em; margin-right: .3em;" aria-hidden="true" focusable="false" data-prefix="fab" data-icon="google-plus" class="svg-inline--fa fa-google-plus fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M256,8C119.1,8,8,119.1,8,256S119.1,504,256,504,504,392.9,504,256,392.9,8,256,8ZM185.3,380a124,124,0,0,1,0-248c31.3,0,60.1,11,83,32.3l-33.6,32.6c-13.2-12.9-31.3-19.1-49.4-19.1-42.9,0-77.2,35.5-77.2,78.1S142.3,334,185.3,334c32.6,0,64.9-19.1,70.1-53.3H185.3V238.1H302.2a109.2,109.2,0,0,1,1.9,20.7c0,70.8-47.5,121.2-118.8,121.2ZM415.5,273.8v35.5H380V273.8H344.5V238.3H380V202.8h35.5v35.5h35.2v35.5Z"></path></svg><small><strong>Log in</strong> with <strong>Google</strong></small></button><br /><style type="text/css">.sign-in-with-apple-button { width: 100%; height: 52px; border-radius: 3px; border: 1px solid black; cursor: pointer; }</style><script src="https://appleid.cdn-apple.com/appleauth/static/jsapi/appleid/1/en_US/appleid.auth.js" type="text/javascript"></script><div class="sign-in-with-apple-button" data-border="false" data-color="white" id="appleid-signin"><span   ="Sign Up with Apple" class="u-fs11"></span></div><script>AppleID.auth.init({ clientId: 'edu.academia.applesignon', scope: 'name email', redirectURI: 'https://www.academia.edu/sessions', state: "ffc79337b9960b4ee24b27c16e8eae7b766a94cd3a5759c35936db69ee5dbae7", });</script><script>// Hacky way of checking if on fast loswp if (window.loswp == null) { (function() { const Google = window?.Aedu?.Auth?.OauthButton?.Login?.Google; const Facebook = window?.Aedu?.Auth?.OauthButton?.Login?.Facebook; if (Google) { new Google({ el: '#login-google-oauth-button', rememberMeCheckboxId: 'remember_me', track: null }); } if (Facebook) { new Facebook({ el: '#login-facebook-oauth-button', rememberMeCheckboxId: 'remember_me', track: null }); } })(); }</script></div></div></div><div class="modal-body"><div class="row"><div class="col-xs-10 col-xs-offset-1"><div class="hr-heading login-hr-heading"><span class="hr-heading-text">or</span></div></div></div></div><div class="modal-body"><div class="row"><div class="col-xs-10 col-xs-offset-1"><form class="js-login-form" action="https://www.academia.edu/sessions" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" autocomplete="off" /><input type="hidden" name="authenticity_token" value="XnOWGC0JWwOYPS0GnFoLukPTOjPZrkt8KLDeLzjgeORJeIsx1iAS70zeTnavVcO+vmh7Cq8bjq+ZDGrZj8+ODA==" autocomplete="off" /><div class="form-group"><label class="control-label" for="login-modal-email-input" style="font-size: 14px;">Email</label><input class="form-control" id="login-modal-email-input" name="login" type="email" /></div><div class="form-group"><label class="control-label" for="login-modal-password-input" style="font-size: 14px;">Password</label><input class="form-control" id="login-modal-password-input" name="password" type="password" /></div><input type="hidden" name="post_login_redirect_url" id="post_login_redirect_url" value="https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH" autocomplete="off" /><div class="checkbox"><label><input type="checkbox" name="remember_me" id="remember_me" value="1" checked="checked" /><small style="font-size: 12px; margin-top: 2px; display: inline-block;">Remember me on this computer</small></label></div><br><input type="submit" name="commit" value="Log In" class="btn btn-primary btn-block btn-lg js-login-submit" data-disable-with="Log In" /></br></form><script>typeof window?.Aedu?.recaptchaManagedForm === 'function' && window.Aedu.recaptchaManagedForm( document.querySelector('.js-login-form'), document.querySelector('.js-login-submit') );</script><small style="font-size: 12px;"><br />or <a data-target="#login-modal-reset-password-container" data-toggle="collapse" href="javascript:void(0)">reset password</a></small><div class="collapse" id="login-modal-reset-password-container"><br /><div class="well margin-0x"><form class="js-password-reset-form" action="https://www.academia.edu/reset_password" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" autocomplete="off" /><input type="hidden" name="authenticity_token" value="PW7+Td63tp7MQYX4dA48uxF/OlSUjIqVI4QohpIJFYkqZeNkJZ7/chii5ohHAfS/7MR7beI5T0aSOJxwJSbjYQ==" autocomplete="off" /><p>Enter the email address you signed up with and we'll email you a reset link.</p><div class="form-group"><input class="form-control" name="email" type="email" /></div><input class="btn btn-primary btn-block g-recaptcha js-password-reset-submit" data-sitekey="6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj" type="submit" value="Email me a link" /></form></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/collapse-45805421cf446ca5adf7aaa1935b08a3a8d1d9a6cc5d91a62a2a3a00b20b3e6a.js"], function() { // from javascript_helper.rb $("#login-modal-reset-password-container").on("shown.bs.collapse", function() { $(this).find("input[type=email]").focus(); }); }); </script> </div></div></div><div class="modal-footer"><div class="text-center"><small style="font-size: 12px;">Need an account? <a rel="nofollow" href="https://www.academia.edu/signup">Click here to sign up</a></small></div></div></div></div></div></div><script>// If we are on subdomain or non-bootstrapped page, redirect to login page instead of showing modal (function(){ if (typeof $ === 'undefined') return; var host = window.location.hostname; if ((host === $domain || host === "www."+$domain) && (typeof $().modal === 'function')) { $("#nav_log_in").click(function(e) { // Don't follow the link and open the modal e.preventDefault(); $("#login-modal").on('shown.bs.modal', function() { $(this).find("#login-modal-email-input").focus() }).modal('show'); }); } })()</script> <div id="fb-root"></div><script>window.fbAsyncInit = function() { FB.init({ appId: "2369844204", version: "v8.0", status: true, cookie: true, xfbml: true }); // Additional initialization code. if (window.InitFacebook) { // facebook.ts already loaded, set it up. window.InitFacebook(); } else { // Set a flag for facebook.ts to find when it loads. window.academiaAuthReadyFacebook = true; } };</script> <div id="google-root"></div><script>window.loadGoogle = function() { if (window.InitGoogle) { // google.ts already loaded, set it up. window.InitGoogle("331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b"); } else { // Set a flag for google.ts to use when it loads. window.GoogleClientID = "331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b"; } };</script> <div class="header--container" id="main-header-container"><div class="header--inner-container header--inner-container-ds2"><div class="header-ds2--left-wrapper"><div class="header-ds2--left-wrapper-inner"><a data-main-header-link-target="logo_home" href="https://www.academia.edu/"><img class="hide-on-desktop-redesign" style="height: 24px; width: 24px;" alt="Academia.edu" src="//a.academia-assets.com/images/academia-logo-redesign-2015-A.svg" width="24" height="24" /><img width="145.2" height="18" class="hide-on-mobile-redesign" style="height: 24px;" alt="Academia.edu" src="//a.academia-assets.com/images/academia-logo-redesign-2015.svg" /></a><div class="header--search-container header--search-container-ds2"><form class="js-SiteSearch-form select2-no-default-pills" action="https://www.academia.edu/search" accept-charset="UTF-8" method="get"><input name="utf8" type="hidden" value="✓" autocomplete="off" /><svg style="width: 14px; height: 14px;" aria-hidden="true" focusable="false" data-prefix="fas" data-icon="search" class="header--search-icon svg-inline--fa fa-search fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M505 442.7L405.3 343c-4.5-4.5-10.6-7-17-7H372c27.6-35.3 44-79.7 44-128C416 93.1 322.9 0 208 0S0 93.1 0 208s93.1 208 208 208c48.3 0 92.7-16.4 128-44v16.3c0 6.4 2.5 12.5 7 17l99.7 99.7c9.4 9.4 24.6 9.4 33.9 0l28.3-28.3c9.4-9.4 9.4-24.6.1-34zM208 336c-70.7 0-128-57.2-128-128 0-70.7 57.2-128 128-128 70.7 0 128 57.2 128 128 0 70.7-57.2 128-128 128z"></path></svg><input class="header--search-input header--search-input-ds2 js-SiteSearch-form-input" data-main-header-click-target="search_input" name="q" placeholder="Search" type="text" /></form></div></div></div><nav class="header--nav-buttons header--nav-buttons-ds2 js-main-nav"><a class="ds2-5-button ds2-5-button--secondary js-header-login-url header-button-ds2 header-login-ds2 hide-on-mobile-redesign" href="https://www.academia.edu/login" rel="nofollow">Log In</a><a class="ds2-5-button ds2-5-button--secondary header-button-ds2 hide-on-mobile-redesign" href="https://www.academia.edu/signup" rel="nofollow">Sign Up</a><button class="header--hamburger-button header--hamburger-button-ds2 hide-on-desktop-redesign js-header-hamburger-button"><div class="icon-bar"></div><div class="icon-bar" style="margin-top: 4px;"></div><div class="icon-bar" style="margin-top: 4px;"></div></button></nav></div><ul class="header--dropdown-container js-header-dropdown"><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/login" rel="nofollow">Log In</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/signup" rel="nofollow">Sign Up</a></li><li class="header--dropdown-row js-header-dropdown-expand-button"><button class="header--dropdown-button">more<svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="caret-down" class="header--dropdown-button-icon svg-inline--fa fa-caret-down fa-w-10" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path fill="currentColor" d="M31.3 192h257.3c17.8 0 26.7 21.5 14.1 34.1L174.1 354.8c-7.8 7.8-20.5 7.8-28.3 0L17.2 226.1C4.6 213.5 13.5 192 31.3 192z"></path></svg></button></li><li><ul class="header--expanded-dropdown-container"><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/about">About</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/press">Press</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://medium.com/@academia">Blog</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/documents">Papers</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/terms">Terms</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/privacy">Privacy</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/copyright">Copyright</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://www.academia.edu/hiring"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="briefcase" class="header--dropdown-row-icon svg-inline--fa fa-briefcase fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M320 336c0 8.84-7.16 16-16 16h-96c-8.84 0-16-7.16-16-16v-48H0v144c0 25.6 22.4 48 48 48h416c25.6 0 48-22.4 48-48V288H320v48zm144-208h-80V80c0-25.6-22.4-48-48-48H176c-25.6 0-48 22.4-48 48v48H48c-25.6 0-48 22.4-48 48v80h512v-80c0-25.6-22.4-48-48-48zm-144 0H192V96h128v32z"></path></svg>We're Hiring!</a></li><li class="header--dropdown-row"><a class="header--dropdown-link" href="https://support.academia.edu/"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="question-circle" class="header--dropdown-row-icon svg-inline--fa fa-question-circle fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M504 256c0 136.997-111.043 248-248 248S8 392.997 8 256C8 119.083 119.043 8 256 8s248 111.083 248 248zM262.655 90c-54.497 0-89.255 22.957-116.549 63.758-3.536 5.286-2.353 12.415 2.715 16.258l34.699 26.31c5.205 3.947 12.621 3.008 16.665-2.122 17.864-22.658 30.113-35.797 57.303-35.797 20.429 0 45.698 13.148 45.698 32.958 0 14.976-12.363 22.667-32.534 33.976C247.128 238.528 216 254.941 216 296v4c0 6.627 5.373 12 12 12h56c6.627 0 12-5.373 12-12v-1.333c0-28.462 83.186-29.647 83.186-106.667 0-58.002-60.165-102-116.531-102zM256 338c-25.365 0-46 20.635-46 46 0 25.364 20.635 46 46 46s46-20.636 46-46c0-25.365-20.635-46-46-46z"></path></svg>Help Center</a></li><li class="header--dropdown-row js-header-dropdown-collapse-button"><button class="header--dropdown-button">less<svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="caret-up" class="header--dropdown-button-icon svg-inline--fa fa-caret-up fa-w-10" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path fill="currentColor" d="M288.662 352H31.338c-17.818 0-26.741-21.543-14.142-34.142l128.662-128.662c7.81-7.81 20.474-7.81 28.284 0l128.662 128.662c12.6 12.599 3.676 34.142-14.142 34.142z"></path></svg></button></li></ul></li></ul></div> <script src="//a.academia-assets.com/assets/webpack_bundles/fast_loswp-bundle-bf3d831cde46cd0e142f29f81a3fc4ce5ab45a404c10c12a480e83de68aff851.js" defer="defer"></script><script>window.loswp = {}; window.loswp.author = 52647603; window.loswp.bulkDownloadFilterCounts = {}; window.loswp.hasDownloadableAttachment = true; window.loswp.hasViewableAttachments = true; // TODO: just use routes for this window.loswp.loginUrl = "https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F49975663%2FVEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH%3Fauto%3Ddownload"; window.loswp.translateUrl = "https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F49975663%2FVEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH%3Fshow_translation%3Dtrue"; window.loswp.previewableAttachments = [{"id":68133202,"identifier":"Attachment_68133202","shouldShowBulkDownload":false}]; window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":49975663,"created_at":"2021-07-16T03:49:04.794-07:00","from_world_paper_id":null,"updated_at":"2021-11-11T01:51:45.502-08:00","_data":{"doi":"10.20858/sjsutst.2021.112.16","abstract":"We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System (ITS) to build a smart city. In this article, three different vehicles: bike, car and truck classification are considered for around 3,000 bikes, 6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract different vehicle dataset's different features without a manual selection of features. The accuracy of CNN is measured in terms of the confidence values of the detected object. The highest confidence value is about 0.99 in the case of the bike category vehicle classification. The automatic vehicle classification supports building an electronic toll collection system and identifying emergency vehicles in the traffic.","publication_date":"2021,,","publication_name":"Scientific Journal of Silesian University of Technology. Series Transport "},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH","broadcastable":true,"draft":false,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [187691426,52647603]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":68133202,"attachmentType":"pdf"}"><img alt="First page of “VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/68133202/mini_magick20210716-1806-1i0u0c5.png?1626433959" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="187691426" href="https://independent.academia.edu/MandalapuSaradaDevi"><img alt="Profile image of Mandalapu Sarada Devi" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Mandalapu Sarada Devi</a><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="52647603" href="https://gtu-in.academia.edu/JANAKTRIVEDI"><img alt="Profile image of JANAK TRIVEDI" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/52647603/40130788/32972826/s65_janak.trivedi.jpg" />JANAK TRIVEDI</a></div><p class="ds-work-card--detail ds2-5-body-sm">2021, Scientific Journal of Silesian University of Technology. Series Transport </p><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System (ITS) to build a smart city. In this article, three different vehicles: bike, car and truck classification are considered for around 3,000 bikes, 6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract different vehicle dataset's different features without a manual selection of features. The accuracy of CNN is measured in terms of the confidence values of the detected object. The highest confidence value is about 0.99 in the case of the bike category vehicle classification. The automatic vehicle classification supports building an electronic toll collection system and identifying emergency vehicles in the traffic.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":68133202,"attachmentType":"pdf","workUrl":"https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":68133202,"attachmentType":"pdf","workUrl":"https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="68133202" data-landing_url="https://www.academia.edu/49975663/VEHICLE_CLASSIFICATION_USING_THE_CONVOLUTION_NEURAL_NETWORK_APPROACH" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="90202241" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/90202241/Vehicular_Detection_and_Classification_for_Intelligent_Transportation_System_A_Deep_Learning_Approach_Using_Faster_R_CNN_Model">Vehicular Detection and Classification for Intelligent Transportation System: A Deep Learning Approach Using Faster R-CNN Model</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="126655250" href="https://independent.academia.edu/CorazonRebong">Corazon Rebong</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International journal of simulation: systems, science & technology, 2019</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicular Detection and Classification for Intelligent Transportation System: A Deep Learning Approach Using Faster R-CNN Model","attachmentId":93829286,"attachmentType":"pdf","work_url":"https://www.academia.edu/90202241/Vehicular_Detection_and_Classification_for_Intelligent_Transportation_System_A_Deep_Learning_Approach_Using_Faster_R_CNN_Model","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/90202241/Vehicular_Detection_and_Classification_for_Intelligent_Transportation_System_A_Deep_Learning_Approach_Using_Faster_R_CNN_Model"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="51054895" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/51054895/A_Model_Based_on_Convolutional_Neural_Network_CNN_for_Vehicle_Classification">A Model Based on Convolutional Neural Network (CNN) for Vehicle Classification</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="202459106" href="https://northsouth.academia.edu/TONMOYROY">TONMOY ROY</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="180841030" href="https://independent.academia.edu/MahdiaAmina">Mahdia Amina</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="99384668" href="https://malaya.academia.edu/FMJavedMehediShamrat">F M Javed Mehedi Shamrat</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="27426166" href="https://independent.academia.edu/KarimAsif">Joyece Jane</a></div><p class="ds-related-work--metadata ds2-5-body-xs">IEEE, 2021</p><p class="ds-related-work--abstract ds2-5-body-sm">The Convolutional Neural Network (CNN) is a form of artificial neural network that has become very popular in computer vision. We proposed a convolutional neural network for classifying common types of vehicles in our country in this paper. Vehicle classification is essential in many applications, including surveillance protection systems and traffic control systems. We raised these concerns and set a goal to find a way to eliminate traffic-related road accidents. The most challenging aspect of computer vision is achieving effective outcomes in order to execute a device due to variations of data shapes and colors. We used three learning methods to identify the vehicle: MobileNetV2, DenseNet, and VGG 19, and demonstrated the methods detection accuracy. Convolutional neural networks are capable of performing all three approaches with grace. The system performs impressively on a real-time standard dataset-the Nepal dataset, which contains 4800 photographs of vehicles. DenseNet has a training accuracy of 94.32 % and a validation accuracy of 95.37%. Furthermore, the VGG 19 has a training accuracy of 91.94 % and a validation accuracy of 92.68 %. The MobileNetV2 architecture has the best accuracy, with a training accuracy of 97.01% and validation accuracy of 98.10%.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Model Based on Convolutional Neural Network (CNN) for Vehicle Classification","attachmentId":68916032,"attachmentType":"pdf","work_url":"https://www.academia.edu/51054895/A_Model_Based_on_Convolutional_Neural_Network_CNN_for_Vehicle_Classification","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/51054895/A_Model_Based_on_Convolutional_Neural_Network_CNN_for_Vehicle_Classification"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="56704372" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/56704372/An_Optimized_Approach_to_Vehicle_Type_Classification_Using_a_Convolutional_Neural_Network">An Optimized Approach to Vehicle-Type Classification Using a Convolutional Neural Network</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="96272921" href="https://independent.academia.edu/NoreenKhan16">Noreen Khan</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Computers, Materials & Continua</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"An Optimized Approach to Vehicle-Type Classification Using a Convolutional Neural Network","attachmentId":71958995,"attachmentType":"pdf","work_url":"https://www.academia.edu/56704372/An_Optimized_Approach_to_Vehicle_Type_Classification_Using_a_Convolutional_Neural_Network","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/56704372/An_Optimized_Approach_to_Vehicle_Type_Classification_Using_a_Convolutional_Neural_Network"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="90641130" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/90641130/A_Novel_Vehicle_Classification_Model_for_Urban_Traffic_Surveillance_Using_the_Deep_Neural_Network_Model">A Novel Vehicle Classification Model for Urban Traffic Surveillance Using the Deep Neural Network Model</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="6065196" href="https://independent.academia.edu/kaurdapinder">dapinder kaur</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Education and Management Engineering, 2016</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Novel Vehicle Classification Model for Urban Traffic Surveillance Using the Deep Neural Network Model","attachmentId":94147965,"attachmentType":"pdf","work_url":"https://www.academia.edu/90641130/A_Novel_Vehicle_Classification_Model_for_Urban_Traffic_Surveillance_Using_the_Deep_Neural_Network_Model","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/90641130/A_Novel_Vehicle_Classification_Model_for_Urban_Traffic_Surveillance_Using_the_Deep_Neural_Network_Model"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="97082644" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/97082644/Vehicle_Detection_for_Vision_Based_Intelligent_Transportation_Systems_Using_Convolutional_Neural_Network_Algorithm">Vehicle Detection for Vision-Based Intelligent Transportation Systems Using Convolutional Neural Network Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="4676562" href="https://redseauniveristy.academia.edu/elmustafasayed">Elmustafa S A Y E D Ali</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="113737" href="https://iium.academia.edu/OTHMANOKHALIFA">OTHMAN O KHALIFA</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Vehicle detection in Intelligent Transportation Systems (ITS) is a key factor ensuring road safety, as it is necessary for the monitoring of vehicle flow, illegal vehicle type detection, incident detection, and vehicle speed estimation. Despite the growing popularity in research, it remains a challenging problem that must be solved. Hardware-based solutions such as radars and LIDAR are been proposed but are too expensive to be maintained and produce little valuable information to human operators at traffic monitoring systems. Software based solutions using traditional algorithms such as Histogram of Gradients (HOG) and Gaussian Mixed Model (GMM) are computationally slow and not suitable for real-time traffic detection. erefore, the paper will review and evaluate different vehicle detection methods. In addition, a method of utilizing Convolutional Neural Network (CNN) is used for the detection of vehicles from roadway camera outputs to apply video processing techniques and extract the desired information. Specifically, the paper utilized the YOLOv5s architecture coupled with k-means algorithm to perform anchor box optimization under different illumination levels. Results from the simulated and evaluated algorithm showed that the proposed model was able to achieve a mAP of 97.8 in the daytime dataset and 95.1 in the nighttime dataset.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle Detection for Vision-Based Intelligent Transportation Systems Using Convolutional Neural Network Algorithm","attachmentId":98803146,"attachmentType":"pdf","work_url":"https://www.academia.edu/97082644/Vehicle_Detection_for_Vision_Based_Intelligent_Transportation_Systems_Using_Convolutional_Neural_Network_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/97082644/Vehicle_Detection_for_Vision_Based_Intelligent_Transportation_Systems_Using_Convolutional_Neural_Network_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="90946549" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/90946549/Vehicle_Type_Classification_Using_Deep_Learning">Vehicle Type Classification Using Deep Learning</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="78516746" href="https://independent.academia.edu/deepakmane5">deepak mane</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Advances in Intelligent Systems and Computing, 2020</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle Type Classification Using Deep Learning","attachmentId":94369432,"attachmentType":"pdf","work_url":"https://www.academia.edu/90946549/Vehicle_Type_Classification_Using_Deep_Learning","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/90946549/Vehicle_Type_Classification_Using_Deep_Learning"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="99372217" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/99372217/A_new_approach_based_on_convolutional_neural_network_and_feature_selection_for_recognizing_vehicle_types">A new approach based on convolutional neural network and feature selection for recognizing vehicle types</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="35734439" href="https://independent.academia.edu/ErgenBurhan">Burhan Ergen</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Iran Journal of Computer Science</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A new approach based on convolutional neural network and feature selection for recognizing vehicle types","attachmentId":100480504,"attachmentType":"pdf","work_url":"https://www.academia.edu/99372217/A_new_approach_based_on_convolutional_neural_network_and_feature_selection_for_recognizing_vehicle_types","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/99372217/A_new_approach_based_on_convolutional_neural_network_and_feature_selection_for_recognizing_vehicle_types"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="100139232" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/100139232/Vehicle_Detection_and_Classification_Using_Deep_Neural_Networks">Vehicle Detection and Classification Using Deep Neural Networks</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="83617235" href="https://nmsu.academia.edu/RiasatKhan">Riasat Khan</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2022 International Conference on Electrical and Information Technology (IEIT)</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle Detection and Classification Using Deep Neural Networks","attachmentId":101044415,"attachmentType":"pdf","work_url":"https://www.academia.edu/100139232/Vehicle_Detection_and_Classification_Using_Deep_Neural_Networks","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/100139232/Vehicle_Detection_and_Classification_Using_Deep_Neural_Networks"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="93292664" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/93292664/A_Vehicle_Detection_Approach_using_Deep_Learning_Methodologies">A Vehicle Detection Approach using Deep Learning Methodologies</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="66264307" href="https://ankara.academia.edu/%C4%B0manAskerbeyli">İman Askerbeyli</a></div><p class="ds-related-work--metadata ds2-5-body-xs">ArXiv, 2018</p><p class="ds-related-work--abstract ds2-5-body-sm">The purpose of this study is to successfully train our vehicle detector using R-CNN, Faster R-CNN deep learning methods on a sample vehicle data sets and to optimize the success rate of the trained detector by providing efficient results for vehicle detection by testing the trained vehicle detector on the test data. The working method consists of six main stages. These are respectively; loading the data set, the design of the convolutional neural network, configuration of training options, training of the Faster R-CNN object detector and evaluation of trained detector. In addition, in the scope of the study, Faster R-CNN, R-CNN deep learning methods were mentioned and experimental analysis comparisons were made with the results obtained from vehicle detection.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Vehicle Detection Approach using Deep Learning Methodologies","attachmentId":96070035,"attachmentType":"pdf","work_url":"https://www.academia.edu/93292664/A_Vehicle_Detection_Approach_using_Deep_Learning_Methodologies","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/93292664/A_Vehicle_Detection_Approach_using_Deep_Learning_Methodologies"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="115285968" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/115285968/Fast_and_Accurate_Deep_Learning_Architecture_on_Vehicle_Type_Recognition">Fast and Accurate Deep Learning Architecture on Vehicle Type Recognition</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="4100949" href="https://mahasarakham.academia.edu/OlarikSurinta">Olarik Surinta</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Current Applied Science and Technology, 2021</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Fast and Accurate Deep Learning Architecture on Vehicle Type Recognition","attachmentId":111737256,"attachmentType":"pdf","work_url":"https://www.academia.edu/115285968/Fast_and_Accurate_Deep_Learning_Architecture_on_Vehicle_Type_Recognition","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/115285968/Fast_and_Accurate_Deep_Learning_Architecture_on_Vehicle_Type_Recognition"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":68133202,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":68133202,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_68133202" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. You can download the paper by clicking the button above.</p></div></div></div></div><div class="ds-sidebar--container js-work-sidebar"><div class="ds-related-content--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="0" data-entity-id="80691601" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/80691601/Large_Scale_Traffic_Surveillance_Vehicle_Detection_and_Classification_Using_Cascade_Classifier_and_Convolutional_Neural_Network">Large Scale Traffic Surveillance :Vehicle Detection and Classification Using Cascade Classifier and Convolutional Neural Network</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="219352128" href="https://independent.academia.edu/ShaifChowdhury">Shaif Chowdhury</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2017</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Large Scale Traffic Surveillance :Vehicle Detection and Classification Using Cascade Classifier and Convolutional Neural Network","attachmentId":86990259,"attachmentType":"pdf","work_url":"https://www.academia.edu/80691601/Large_Scale_Traffic_Surveillance_Vehicle_Detection_and_Classification_Using_Cascade_Classifier_and_Convolutional_Neural_Network","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/80691601/Large_Scale_Traffic_Surveillance_Vehicle_Detection_and_Classification_Using_Cascade_Classifier_and_Convolutional_Neural_Network"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="1" data-entity-id="113935455" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/113935455/Vehicle_Type_Detection_by_Convolutional_Neural_Networks">Vehicle Type Detection by Convolutional Neural Networks</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32693197" href="https://uma.academia.edu/EzequielL%C3%B3pezRubio">Ezequiel López-Rubio</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Biomedical Applications Based on Natural and Artificial Computing, 2017</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle Type Detection by Convolutional Neural Networks","attachmentId":110767194,"attachmentType":"pdf","work_url":"https://www.academia.edu/113935455/Vehicle_Type_Detection_by_Convolutional_Neural_Networks","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/113935455/Vehicle_Type_Detection_by_Convolutional_Neural_Networks"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="2" data-entity-id="103380713" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/103380713/Vehicle_detection_systems_for_intelligent_driving_using_deep_convolutional_neural_networks">Vehicle detection systems for intelligent driving using deep convolutional neural networks</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="40045720" href="https://independent.academia.edu/Abiyev">Rahib Abiyev</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Discover Artificial Intelligence</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle detection systems for intelligent driving using deep convolutional neural networks","attachmentId":103402835,"attachmentType":"pdf","work_url":"https://www.academia.edu/103380713/Vehicle_detection_systems_for_intelligent_driving_using_deep_convolutional_neural_networks","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/103380713/Vehicle_detection_systems_for_intelligent_driving_using_deep_convolutional_neural_networks"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="3" data-entity-id="80176070" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/80176070/A_Comparitive_Study_of_Convolutional_Neural_Network_Models_for_Detection_Classification_and_Counting_of_Vehicles_in_Traffic">A Comparitive Study of Convolutional Neural Network Models for Detection, Classification and Counting of Vehicles in Traffic</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="45702421" href="https://independent.academia.edu/AziziAbdullah3">Azizi Abdullah</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2020</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Comparitive Study of Convolutional Neural Network Models for Detection, Classification and Counting of Vehicles in Traffic","attachmentId":86645411,"attachmentType":"pdf","work_url":"https://www.academia.edu/80176070/A_Comparitive_Study_of_Convolutional_Neural_Network_Models_for_Detection_Classification_and_Counting_of_Vehicles_in_Traffic","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/80176070/A_Comparitive_Study_of_Convolutional_Neural_Network_Models_for_Detection_Classification_and_Counting_of_Vehicles_in_Traffic"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="4" data-entity-id="91029771" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/91029771/To_Identify_and_Recognize_the_Object_for_Traffic_Analysis_System_using_Deep_Learning">To Identify and Recognize the Object for Traffic Analysis System using Deep Learning</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="191466673" href="https://independent.academia.edu/Sakshisinha50">Sakshi sinha</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Innovative Technology and Exploring Engineering, 2019</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"To Identify and Recognize the Object for Traffic Analysis System using Deep Learning","attachmentId":94431075,"attachmentType":"pdf","work_url":"https://www.academia.edu/91029771/To_Identify_and_Recognize_the_Object_for_Traffic_Analysis_System_using_Deep_Learning","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/91029771/To_Identify_and_Recognize_the_Object_for_Traffic_Analysis_System_using_Deep_Learning"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="5" data-entity-id="43807151" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/43807151/IJERT_Real_Time_Road_Surveillance_and_Vehicle_Detection_using_Deep_Learning">IJERT-Real Time Road Surveillance and Vehicle Detection using Deep Learning</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="109571315" href="https://independent.academia.edu/IJERTORG">IJERT Journal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Engineering Research and Technology (IJERT), 2020</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"IJERT-Real Time Road Surveillance and Vehicle Detection using Deep Learning","attachmentId":64125003,"attachmentType":"pdf","work_url":"https://www.academia.edu/43807151/IJERT_Real_Time_Road_Surveillance_and_Vehicle_Detection_using_Deep_Learning","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/43807151/IJERT_Real_Time_Road_Surveillance_and_Vehicle_Detection_using_Deep_Learning"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="6" data-entity-id="84937791" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/84937791/Deep_Learning_Based_Vehicle_Classification_for_Low_Quality_Images">Deep Learning-Based Vehicle Classification for Low Quality Images</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="99717787" href="https://atilim.academia.edu/OzgenSari">Ozgen Sari</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Sensors</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Deep Learning-Based Vehicle Classification for Low Quality Images","attachmentId":89793246,"attachmentType":"pdf","work_url":"https://www.academia.edu/84937791/Deep_Learning_Based_Vehicle_Classification_for_Low_Quality_Images","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/84937791/Deep_Learning_Based_Vehicle_Classification_for_Low_Quality_Images"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="7" data-entity-id="83838703" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/83838703/Classification_of_Traffic_Vehicle_Density_Using_Deep_Learning">Classification of Traffic Vehicle Density Using Deep Learning</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="36917522" href="https://independent.academia.edu/AgusHarjoko">Agus Harjoko</a></div><p class="ds-related-work--metadata ds2-5-body-xs">IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2020</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Classification of Traffic Vehicle Density Using Deep Learning","attachmentId":89056188,"attachmentType":"pdf","work_url":"https://www.academia.edu/83838703/Classification_of_Traffic_Vehicle_Density_Using_Deep_Learning","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/83838703/Classification_of_Traffic_Vehicle_Density_Using_Deep_Learning"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="8" data-entity-id="121436455" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/121436455/A_Fast_and_Accurate_Real_Time_Vehicle_Detection_Method_Using_Deep_Learning_for_Unconstrained_Environments">A Fast and Accurate Real-Time Vehicle Detection Method Using Deep Learning for Unconstrained Environments</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="300174126" href="https://independent.academia.edu/UzairKhan696">Uzair Khan</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Applied Sciences</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Fast and Accurate Real-Time Vehicle Detection Method Using Deep Learning for Unconstrained Environments","attachmentId":116311986,"attachmentType":"pdf","work_url":"https://www.academia.edu/121436455/A_Fast_and_Accurate_Real_Time_Vehicle_Detection_Method_Using_Deep_Learning_for_Unconstrained_Environments","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/121436455/A_Fast_and_Accurate_Real_Time_Vehicle_Detection_Method_Using_Deep_Learning_for_Unconstrained_Environments"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="9" data-entity-id="87042948" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/87042948/Multilayer_vehicle_classification_integrated_with_single_frame_optimized_object_detection_framework_using_CNN_based_deep_learning_architecture">Multilayer vehicle classification integrated with single frame optimized object detection framework using CNN based deep learning architecture</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="88072562" href="https://du-in.academia.edu/DharmendraKumarMahato">Dharmendra Kumar Mahato</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2018</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Multilayer vehicle classification integrated with single frame optimized object detection framework using CNN based deep learning architecture","attachmentId":91364619,"attachmentType":"pdf","work_url":"https://www.academia.edu/87042948/Multilayer_vehicle_classification_integrated_with_single_frame_optimized_object_detection_framework_using_CNN_based_deep_learning_architecture","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/87042948/Multilayer_vehicle_classification_integrated_with_single_frame_optimized_object_detection_framework_using_CNN_based_deep_learning_architecture"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="10" data-entity-id="33300656" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/33300656/Vehicle_Make_and_Model_Classification_Using_Convolutional_Neural_Networks">Vehicle Make and Model Classification Using Convolutional Neural Networks</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="24493864" href="https://independent.academia.edu/SyedHasibAkhterFaruqui">Syed Hasib Akhter Faruqui</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle Make and Model Classification Using Convolutional Neural Networks","attachmentId":53365961,"attachmentType":"pdf","work_url":"https://www.academia.edu/33300656/Vehicle_Make_and_Model_Classification_Using_Convolutional_Neural_Networks","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/33300656/Vehicle_Make_and_Model_Classification_Using_Convolutional_Neural_Networks"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="11" data-entity-id="125474686" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/125474686/Object_Detection_and_Classification_Through_Deep_Learning_Approaches">Object Detection and Classification Through Deep Learning Approaches</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="321190784" href="https://independent.academia.edu/DrSHRWANRAM">Dr. SHRWAN RAM</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of emerging technologies and innovative research, 2018</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Object Detection and Classification Through Deep Learning Approaches","attachmentId":119510861,"attachmentType":"pdf","work_url":"https://www.academia.edu/125474686/Object_Detection_and_Classification_Through_Deep_Learning_Approaches","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/125474686/Object_Detection_and_Classification_Through_Deep_Learning_Approaches"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="12" data-entity-id="90959603" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/90959603/Automated_Vehicle_Recognition_with_Deep_Convolutional_Neural_Networks">Automated Vehicle Recognition with Deep Convolutional Neural Networks</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="30575540" href="https://iastate.academia.edu/AnujSharma">Anuj Sharma</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Transportation Research Record: Journal of the Transportation Research Board, 2017</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Automated Vehicle Recognition with Deep Convolutional Neural Networks","attachmentId":94379609,"attachmentType":"pdf","work_url":"https://www.academia.edu/90959603/Automated_Vehicle_Recognition_with_Deep_Convolutional_Neural_Networks","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/90959603/Automated_Vehicle_Recognition_with_Deep_Convolutional_Neural_Networks"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="13" data-entity-id="123147363" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/123147363/Convolutional_Neural_Network_Based_Vehicle_Classification_in_Low_Quality_Imaging_Conditions_for_Internet_of_Things_Devices">Convolutional Neural Network-Based Vehicle Classification in Low-Quality Imaging Conditions for Internet of Things Devices</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="251811633" href="https://independent.academia.edu/MDerawi">Mohammad Derawi</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Sustainability</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Convolutional Neural Network-Based Vehicle Classification in Low-Quality Imaging Conditions for Internet of Things Devices","attachmentId":117650814,"attachmentType":"pdf","work_url":"https://www.academia.edu/123147363/Convolutional_Neural_Network_Based_Vehicle_Classification_in_Low_Quality_Imaging_Conditions_for_Internet_of_Things_Devices","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/123147363/Convolutional_Neural_Network_Based_Vehicle_Classification_in_Low_Quality_Imaging_Conditions_for_Internet_of_Things_Devices"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="14" data-entity-id="43669902" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/43669902/OBJECT_DETECTION_IN_TRAFFIC_SCENARIOS_A_COMPARISON_OF_TRADITIONAL_AND_DEEP_LEARNING_APPROACHES">OBJECT DETECTION IN TRAFFIC SCENARIOS -A COMPARISON OF TRADITIONAL AND DEEP LEARNING APPROACHES</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="15689241" href="https://independent.academia.edu/ComputerScienceInformationTechnologyCSIT">Computer Science & Information Technology (CS & IT) Computer Science Conference Proceedings (CSCP)</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"OBJECT DETECTION IN TRAFFIC SCENARIOS -A COMPARISON OF TRADITIONAL AND DEEP LEARNING APPROACHES","attachmentId":63971211,"attachmentType":"pdf","work_url":"https://www.academia.edu/43669902/OBJECT_DETECTION_IN_TRAFFIC_SCENARIOS_A_COMPARISON_OF_TRADITIONAL_AND_DEEP_LEARNING_APPROACHES","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/43669902/OBJECT_DETECTION_IN_TRAFFIC_SCENARIOS_A_COMPARISON_OF_TRADITIONAL_AND_DEEP_LEARNING_APPROACHES"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="15" data-entity-id="112084286" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/112084286/Vehicle_Detection_and_Identification_Using_Computer_Vision_Technology_with_the_Utilization_of_the_YOLOv8_Deep_Learning_Method">Vehicle Detection and Identification Using Computer Vision Technology with the Utilization of the YOLOv8 Deep Learning Method</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="218588178" href="https://independent.academia.edu/TELAUMBANUAPASRAH">PASRAH TELAUMBANUA</a></div><p class="ds-related-work--metadata ds2-5-body-xs">sinkron</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle Detection and Identification Using Computer Vision Technology with the Utilization of the YOLOv8 Deep Learning Method","attachmentId":109424272,"attachmentType":"pdf","work_url":"https://www.academia.edu/112084286/Vehicle_Detection_and_Identification_Using_Computer_Vision_Technology_with_the_Utilization_of_the_YOLOv8_Deep_Learning_Method","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/112084286/Vehicle_Detection_and_Identification_Using_Computer_Vision_Technology_with_the_Utilization_of_the_YOLOv8_Deep_Learning_Method"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="16" data-entity-id="120891378" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/120891378/An_efficient_object_detection_by_autonomous_vehicle_using_deep_learning">An efficient object detection by autonomous vehicle using deep learning</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="163474776" href="https://independent.academia.edu/JournalIJECE">International Journal of Electrical and Computer Engineering (IJECE)</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Electrical and Computer Engineering (IJECE), 2024</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"An efficient object detection by autonomous vehicle using deep learning","attachmentId":115901107,"attachmentType":"pdf","work_url":"https://www.academia.edu/120891378/An_efficient_object_detection_by_autonomous_vehicle_using_deep_learning","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/120891378/An_efficient_object_detection_by_autonomous_vehicle_using_deep_learning"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="17" data-entity-id="87642621" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/87642621/Comparative_Analysis_of_Deep_Learning_Models_for_Vehicle_Detection">Comparative Analysis of Deep Learning Models for Vehicle Detection</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="47939579" href="https://independent.academia.edu/RendiNurcahyo">Rendi Nurcahyo</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Systems Engineering and Information Technology (JOSEIT), 2022</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Comparative Analysis of Deep Learning Models for Vehicle Detection","attachmentId":91796036,"attachmentType":"pdf","work_url":"https://www.academia.edu/87642621/Comparative_Analysis_of_Deep_Learning_Models_for_Vehicle_Detection","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/87642621/Comparative_Analysis_of_Deep_Learning_Models_for_Vehicle_Detection"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="18" data-entity-id="33495873" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/33495873/Moving_Vehicle_Detection_and_Information_Extraction_Based_on_Deep_Neural_Network">Moving Vehicle Detection and Information Extraction Based on Deep Neural Network</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="37626596" href="https://dgist.academia.edu/IhsanUllahKhan">Ihsan Ullah Khan</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Moving Vehicle Detection and Information Extraction Based on Deep Neural Network","attachmentId":53535636,"attachmentType":"pdf","work_url":"https://www.academia.edu/33495873/Moving_Vehicle_Detection_and_Information_Extraction_Based_on_Deep_Neural_Network","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/33495873/Moving_Vehicle_Detection_and_Information_Extraction_Based_on_Deep_Neural_Network"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="19" data-entity-id="33495877" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/33495877/Vehicle_Make_and_Model_Recognition_System_based_on_Convolutional_Neural_Network_Vehicle_Make_and_Model_Recognition_System_based_on_Convolutional_Neural_Network">Vehicle Make and Model Recognition System based on Convolutional Neural Network Vehicle Make and Model Recognition System based on Convolutional Neural Network</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="37626596" href="https://dgist.academia.edu/IhsanUllahKhan">Ihsan Ullah Khan</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vehicle Make and Model Recognition System based on Convolutional Neural Network Vehicle Make and Model Recognition System based on Convolutional Neural Network","attachmentId":53535640,"attachmentType":"pdf","work_url":"https://www.academia.edu/33495877/Vehicle_Make_and_Model_Recognition_System_based_on_Convolutional_Neural_Network_Vehicle_Make_and_Model_Recognition_System_based_on_Convolutional_Neural_Network","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/33495877/Vehicle_Make_and_Model_Recognition_System_based_on_Convolutional_Neural_Network_Vehicle_Make_and_Model_Recognition_System_based_on_Convolutional_Neural_Network"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div><div class="ds-related-content--container"><h2 class="ds-related-content--heading">Related topics</h2><div class="ds-research-interests--pills-container"><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="465" href="https://www.academia.edu/Documents/in/Artificial_Intelligence">Artificial Intelligence</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="854" href="https://www.academia.edu/Documents/in/Computer_Vision">Computer Vision</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="1185" href="https://www.academia.edu/Documents/in/Image_Processing">Image Processing</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="4038" href="https://www.academia.edu/Documents/in/Real_Time_Computing">Real Time Computing</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="6203" href="https://www.academia.edu/Documents/in/Electronics_and_Telecommunication_Engineering">Electronics & Telecommunication ...</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="9038" href="https://www.academia.edu/Documents/in/Digital_Signal_Processing">Digital Signal Processing</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="9589" href="https://www.academia.edu/Documents/in/Intelligent_Transportation_Systems">Intelligent Transportation Systems</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="15665" href="https://www.academia.edu/Documents/in/Video_Processing">Video Processing</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="60144" href="https://www.academia.edu/Documents/in/Automotive">Automotive</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="81182" href="https://www.academia.edu/Documents/in/Deep_Learning">Deep Learning</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="99614" href="https://www.academia.edu/Documents/in/Image_and_Video_Processing">Image and Video Processing</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="161944" href="https://www.academia.edu/Documents/in/Tracking_Vehicles_in_Real_Time">Tracking Vehicles in Real Time</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="204314" href="https://www.academia.edu/Documents/in/Real-Time_Analysis">Real-Time Analysis</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="326814" href="https://www.academia.edu/Documents/in/Trucks">Trucks</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="742635" href="https://www.academia.edu/Documents/in/Vehicle_Classification">Vehicle Classification</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="922055" href="https://www.academia.edu/Documents/in/Electronics_and_Communications_Engineering">Electronics and Communications E...</a><a class="js-related-research-interest ds-research-interests--pill" data-entity-id="925569" href="https://www.academia.edu/Documents/in/Car_Image_Classification">Car Image Classification</a></div></div></div></div></div><div class="footer--content"><ul class="footer--main-links hide-on-mobile"><li><a href="https://www.academia.edu/about">About</a></li><li><a href="https://www.academia.edu/press">Press</a></li><li><a rel="nofollow" href="https://medium.com/academia">Blog</a></li><li><a href="https://www.academia.edu/documents">Papers</a></li><li><a href="https://www.academia.edu/topics">Topics</a></li><li><a href="https://www.academia.edu/hiring"><svg style="width: 13px; height: 13px; position: relative; bottom: -1px;" aria-hidden="true" focusable="false" data-prefix="fas" data-icon="briefcase" class="svg-inline--fa fa-briefcase fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M320 336c0 8.84-7.16 16-16 16h-96c-8.84 0-16-7.16-16-16v-48H0v144c0 25.6 22.4 48 48 48h416c25.6 0 48-22.4 48-48V288H320v48zm144-208h-80V80c0-25.6-22.4-48-48-48H176c-25.6 0-48 22.4-48 48v48H48c-25.6 0-48 22.4-48 48v80h512v-80c0-25.6-22.4-48-48-48zm-144 0H192V96h128v32z"></path></svg> <strong>We're Hiring!</strong></a></li><li><a href="https://support.academia.edu/"><svg style="width: 12px; height: 12px; position: relative; bottom: -1px;" aria-hidden="true" focusable="false" data-prefix="fas" data-icon="question-circle" class="svg-inline--fa fa-question-circle fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M504 256c0 136.997-111.043 248-248 248S8 392.997 8 256C8 119.083 119.043 8 256 8s248 111.083 248 248zM262.655 90c-54.497 0-89.255 22.957-116.549 63.758-3.536 5.286-2.353 12.415 2.715 16.258l34.699 26.31c5.205 3.947 12.621 3.008 16.665-2.122 17.864-22.658 30.113-35.797 57.303-35.797 20.429 0 45.698 13.148 45.698 32.958 0 14.976-12.363 22.667-32.534 33.976C247.128 238.528 216 254.941 216 296v4c0 6.627 5.373 12 12 12h56c6.627 0 12-5.373 12-12v-1.333c0-28.462 83.186-29.647 83.186-106.667 0-58.002-60.165-102-116.531-102zM256 338c-25.365 0-46 20.635-46 46 0 25.364 20.635 46 46 46s46-20.636 46-46c0-25.365-20.635-46-46-46z"></path></svg> <strong>Help Center</strong></a></li></ul><ul class="footer--research-interests"><li>Find new research papers in:</li><li><a href="https://www.academia.edu/Documents/in/Physics">Physics</a></li><li><a href="https://www.academia.edu/Documents/in/Chemistry">Chemistry</a></li><li><a href="https://www.academia.edu/Documents/in/Biology">Biology</a></li><li><a href="https://www.academia.edu/Documents/in/Health_Sciences">Health Sciences</a></li><li><a href="https://www.academia.edu/Documents/in/Ecology">Ecology</a></li><li><a href="https://www.academia.edu/Documents/in/Earth_Sciences">Earth Sciences</a></li><li><a href="https://www.academia.edu/Documents/in/Cognitive_Science">Cognitive Science</a></li><li><a href="https://www.academia.edu/Documents/in/Mathematics">Mathematics</a></li><li><a href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a></li></ul><ul class="footer--legal-links hide-on-mobile"><li><a href="https://www.academia.edu/terms">Terms</a></li><li><a href="https://www.academia.edu/privacy">Privacy</a></li><li><a href="https://www.academia.edu/copyright">Copyright</a></li><li>Academia ©2024</li></ul></div> </body> </html>