Poly-CAM: High resolution Class Activation Map for Convolutional Neural Networks

Poly-CAM: High resolution Class Activation Map for Convolutional Neural Networks | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Poly-CAM: High resolution Class Activation Map for Convolutional Neural Networks Alexandre Englebert, Olivier Cornu, Christophe De Vleeschouwer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4129485/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2024 Read the published version in Machine Vision and Applications → Version 1 posted 9 You are reading this latest preprint version Abstract The demand for explainable AI continues to rise alongside advancements in deep learning technology. Existing methods such as convolutional neural networks often struggle to accurately pinpoint the image features justifying a network's prediction due to low-resolution saliency maps (e.g., CAM), smooth visualizations from perturbation-based techniques, or numerous isolated peaky spots in gradient-based approaches. In response, our work seeks to merge information from earlier and later layers within the network to create high-resolution class activation maps that not only maintain a level of competitiveness with previous art in terms of insertion-deletion faithfulness metrics but also significantly surpass it regarding the precision of localizing class-specific features. Explanable AI deep learning convolutional neural networks feature localization high resolution Class Activation Map Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2024 Read the published version in Machine Vision and Applications → Version 1 posted Editorial decision: Revision requested 15 May, 2024 Reviews received at journal 14 May, 2024 Reviewers agreed at journal 18 Apr, 2024 Reviews received at journal 18 Apr, 2024 Reviewers agreed at journal 18 Apr, 2024 Reviewers invited by journal 18 Apr, 2024 Submission checks completed at journal 19 Mar, 2024 Editor assigned by journal 19 Mar, 2024 First submitted to journal 19 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4129485","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281593578,"identity":"5d39f00c-1c0d-4ed5-b099-7c1f759765bc","order_by":0,"name":"Alexandre Englebert","email":"data:image/png;base64,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","orcid":"","institution":"Université Catholique de Louvain","correspondingAuthor":true,"prefix":"","firstName":"Alexandre","middleName":"","lastName":"Englebert","suffix":""},{"id":281593579,"identity":"7a791b08-7fd3-446e-a60e-9b5926f8b8d5","order_by":1,"name":"Olivier Cornu","email":"","orcid":"","institution":"Cliniques Universitaires Saint-Luc","correspondingAuthor":false,"prefix":"","firstName":"Olivier","middleName":"","lastName":"Cornu","suffix":""},{"id":281593580,"identity":"5898d0d7-ce68-4570-b016-47885e6269dd","order_by":2,"name":"Christophe De Vleeschouwer","email":"","orcid":"","institution":"Université Catholique de Louvain","correspondingAuthor":false,"prefix":"","firstName":"Christophe","middleName":"","lastName":"De Vleeschouwer","suffix":""}],"badges":[],"createdAt":"2024-03-19 10:28:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4129485/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4129485/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00138-024-01567-7","type":"published","date":"2024-07-01T19:34:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":61524769,"identity":"59d0ddef-3761-4724-a11e-215b241cb5f0","added_by":"auto","created_at":"2024-07-31 19:34:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6233616,"visible":true,"origin":"","legend":"","description":"","filename":"PolycamMachineVisionApplications1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4129485/v1_covered_61c49ac1-3be2-4fcc-98be-9fdaac0120b3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Poly-CAM: High resolution Class Activation Map for Convolutional Neural Networks","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"machine-vision-and-applications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mvap","sideBox":"Learn more about [Machine Vision and Applications](https://www.springer.com/journal/138)","snPcode":"138","submissionUrl":"https://submission.springernature.com/new-submission/138/3","title":"Machine Vision and Applications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Explanable AI, deep learning, convolutional neural networks, feature localization, high resolution Class Activation Map","lastPublishedDoi":"10.21203/rs.3.rs-4129485/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4129485/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The demand for explainable AI continues to rise alongside advancements in deep learning technology. 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