Going More Deeper With Convolutions for Network in Network

Going More Deeper With Convolutions for Network in Network | 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 Going More Deeper With Convolutions for Network in Network neji kouka, jawaher ben khalfa, jalel eddine hajlaoui This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5421323/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Network in Network is an important extension of the deep convolution neural network that uses a shallow multilayer perceptron (MLP), a nonlinear function, to replace the linear filter. In this article, we propose to replace convolution layers with convolution modules. The main feature of this architecture is the improved utilization of computing resources inside the network. This has been achieved through a carefully crafted design that allows for increased network depth and width while keeping the compute budget constant. The experimental results on the CIFAR10 dataset demonstrate the effectiveness of the proposed method Convolutional Neural Networks (CNNs) Image recognition Network in Network (NiN). Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5421323","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":376698214,"identity":"f0bb6ab5-40f8-4f2e-9b27-0d22d6a3cc41","order_by":0,"name":"neji kouka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYHCChIMNDAwGDPKHDz4A8nj4iNciwZZsANLCRow1jBAtPGYSIB5BLebsDQ8Pzqg4bMw/u8es8muOnQwbA/PDRzfwaLHsOZBwcMOZw2YSd46V3Zbdlgx0GJuxcQ4eLQY3EhIOPmw7bMNwIHnbbcltzEAtPGzSeLXcfwDRIn8gwaxYcls9EVpuAENsY9thM4MbKWaMH7cdJkLLGaDDZpxJNzY8cyxZmnHbcR42ZkJ+OX4m+WNPhbXhvOPNBz/+3FZtz8/e/PAxPi3AuEuAM5l5wCRe5SDAfgDOZPxBUPUoGAWjYBSMRAAAaZ1RXJqttAQAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"neji","middleName":"","lastName":"kouka","suffix":""},{"id":376698215,"identity":"b6321f14-7ee5-4e3c-88df-6a62bc50a62b","order_by":1,"name":"jawaher ben khalfa","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"jawaher","middleName":"ben","lastName":"khalfa","suffix":""},{"id":376698216,"identity":"015b4c4d-100e-43ca-9b3c-ed035a32eef8","order_by":2,"name":"jalel eddine hajlaoui","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"jalel","middleName":"eddine","lastName":"hajlaoui","suffix":""}],"badges":[],"createdAt":"2024-11-09 10:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5421323/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5421323/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68775341,"identity":"3ca6aa09-1b0b-4df4-a858-33502f931ecc","added_by":"auto","created_at":"2024-11-12 01:30:59","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":268173,"visible":true,"origin":"","legend":"","description":"","filename":"latexpaper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5421323/v1_covered_fed35a8d-be6e-43c1-9710-33950a2a5679.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eGoing More Deeper With Convolutions for Network in Network\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Convolutional Neural Networks (CNNs), Image recognition, Network in Network (NiN).","lastPublishedDoi":"10.21203/rs.3.rs-5421323/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5421323/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Network in Network is an important extension of the deep convolution neural network that uses a shallow multilayer perceptron (MLP), a nonlinear function, to replace the linear filter. 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