Optimizing Image Classification Models for Cloud Infrastructure with Elastic Scaling

Optimizing Image Classification Models for Cloud Infrastructure with Elastic Scaling | 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 Optimizing Image Classification Models for Cloud Infrastructure with Elastic Scaling Wei Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6060053/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 Advances in image classification have led to significant improvements in various applications, yet challenges remain in optimizing these models for cloud infrastructures. Fluctuating workloads and the need for efficient resource allocation complicate the deployment of high-performing models. We propose a novel framework that enhances image classification performance specifically within cloud environments through Elastic Scaling. This approach leverages a modular architecture, facilitating real-time adjustments to computing resources based on demand and complexity of the models being utilized. Our methodology incorporates diverse data preprocessing techniques and evaluates multiple model architectures to strike a balance between accuracy and operational efficiency. Extensive experiments conducted across various datasets demonstrate the effectiveness of our solution, showcasing considerable enhancements in classification performance and substantial reductions in operational costs tied to cloud infrastructure. The findings highlight improvements in response times and resource utilization, creating an adaptive framework that effectively addresses differing image processing requirements. This work offers a comprehensive solution aimed at optimizing cloud-based image classification tasks while maximizing performance and efficiency. Computer Architecture and Engineering Image classification model Cloud Service Full Text Additional Declarations The authors declare no competing interests. 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. 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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-6060053","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":417765949,"identity":"aa3a32dd-0b57-4973-bedf-c9af354f5efc","order_by":0,"name":"Wei Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYLCCBww2pGpJYEgjXcthElQb3MgxfJBQc15et/34w8cFDHZyug2EtRgbJBy7bbjtTEKy8QyGZGOzAwS0mN1OS5NIYLvNuO1AwjFpHoYDiduI0JL+I+HfOftt5x+2Easl+RhDYhtQ5Y1kNuK02N9/fFgisS85eduNZ8zGPAZE+EWy52Djhw/f7Gy3nU9/+Jinwk6OoBY0YECa8lEwCkbBKBgFOAAAa65FFiRbEvsAAAAASUVORK5CYII=","orcid":"","institution":"Amazon","correspondingAuthor":true,"prefix":"","firstName":"Wei","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2025-02-19 03:09:15","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6060053/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6060053/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76723351,"identity":"d7895d47-683a-4a54-b90e-798aae34377a","added_by":"auto","created_at":"2025-02-20 05:04:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":661075,"visible":true,"origin":"","legend":"","description":"","filename":"OptimizingImageClassificationModelsforCloudInfrastructurewithElasticScaling.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6060053/v1_covered_675f1563-f9ab-42b0-8625-77b99e141924.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eOptimizing Image Classification Models for Cloud Infrastructure with Elastic Scaling\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":true,"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":"Image classification model, Cloud Service","lastPublishedDoi":"10.21203/rs.3.rs-6060053/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6060053/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAdvances in image classification have led to significant improvements in various applications, yet challenges remain in optimizing these models for cloud infrastructures. 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