Multiple Channel GCN with Multiple Directional Gaussian for Porcelain Microscopic Image Classification

Multiple Channel GCN with Multiple Directional Gaussian for Porcelain Microscopic Image Classification | 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 Article Multiple Channel GCN with Multiple Directional Gaussian for Porcelain Microscopic Image Classification Xinda Liu, Yangyang Liu, Jinkai Zhen, Guohua Geng, Wuyang Shui This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5867069/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jun, 2025 Read the published version in npj Heritage Science → Version 1 posted 6 You are reading this latest preprint version Abstract Porcelain fragment classification is crucial for cultural relic restoration. Traditional manual methods relying on macroscopic features struggle to balance accuracy and efficiency. This study proposes a multi-channel graph convolutional network (GCN) architecture integrated with multi-directional Gaussian filtering. First, images are converted into graph structures and processed with multidirectional Gaussian filtering to reduce noise while preserving texture details. The proposed multi-channel GCN extracts rich interconnected features from multiple perspectives. Experimental results achieved 93.33% accuracy, outperforming ResNet50 by 3.33% and DenseNet121 by 2.80%. This approach effectively addresses noise interference and uneven feature distribution in microscopic images. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Jun, 2025 Read the published version in npj Heritage Science → Version 1 posted Editorial decision: Accepted 14 Apr, 2025 Reviews received at journal 10 Apr, 2025 Reviewers agreed at journal 03 Apr, 2025 Reviewers invited by journal 03 Apr, 2025 Submission checks completed at journal 01 Apr, 2025 First submitted to journal 21 Mar, 2025 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-5867069","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":438162589,"identity":"8b09c37a-fd24-4da5-b0e5-f77c3ea16ee2","order_by":0,"name":"Xinda Liu","email":"","orcid":"","institution":"Northwest University","correspondingAuthor":false,"prefix":"","firstName":"Xinda","middleName":"","lastName":"Liu","suffix":""},{"id":438162590,"identity":"bdfd8d10-aa82-4c76-b23e-a1e1307bf9fe","order_by":1,"name":"Yangyang Liu","email":"","orcid":"","institution":"Northwest University","correspondingAuthor":false,"prefix":"","firstName":"Yangyang","middleName":"","lastName":"Liu","suffix":""},{"id":438162592,"identity":"64376638-b973-42cb-94d6-ed4f6dbaf124","order_by":2,"name":"Jinkai Zhen","email":"","orcid":"","institution":"Northwest University","correspondingAuthor":false,"prefix":"","firstName":"Jinkai","middleName":"","lastName":"Zhen","suffix":""},{"id":438162594,"identity":"4be271cf-d1dd-4a04-918f-f63c41242bd8","order_by":3,"name":"Guohua Geng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYDACCTBpA+HwkKAljXQth0nQIh/dfvFxwa/zeQY3EhgfvG1jkDcnpMXwzpli45l9t4uBWpgN57YxGO5sIKRlRk6aNG/P7cRtNxLYpHnbGBIMDhDWkv6bt+ccSAv7b6K0yEukH2Pm+XEAbAszUVoMJHKYpXkbkhP3n3nYLDnnnIThBoK2zEh/+Jnnj13izPbkgx/elNnIE7blAI8BA2MbiMnYwACLJvy2NLA/YGD4Q1jhKBgFo2AUjGAAAHTaRAgfwb1YAAAAAElFTkSuQmCC","orcid":"","institution":"Northwest University","correspondingAuthor":true,"prefix":"","firstName":"Guohua","middleName":"","lastName":"Geng","suffix":""},{"id":438162597,"identity":"480ef7ed-855d-4067-883d-3ee97dd7f374","order_by":4,"name":"Wuyang Shui","email":"","orcid":"","institution":"Alder Hey Children's NHS Foundation Trust","correspondingAuthor":false,"prefix":"","firstName":"Wuyang","middleName":"","lastName":"Shui","suffix":""}],"badges":[],"createdAt":"2025-01-20 15:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5867069/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5867069/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s40494-025-01716-9","type":"published","date":"2025-06-10T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84727159,"identity":"3b431a3f-b143-4a49-a8ce-7c9e57fd6459","added_by":"auto","created_at":"2025-06-16 16:09:15","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1149828,"visible":true,"origin":"","legend":"","description":"","filename":"heritagescienceceramicrevise.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5867069/v1_covered_5e467fc0-8dcb-4759-8a8a-0e5c163c4a8e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multiple Channel GCN with Multiple Directional Gaussian for Porcelain Microscopic Image Classification","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":"npj-heritage-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hsci","sideBox":"Learn more about [Heritage Science](http://heritagesciencejournal.springeropen.com)","snPcode":"40494","submissionUrl":"https://submission.nature.com/new-submission/40494/3","title":"npj Heritage Science","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5867069/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5867069/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePorcelain fragment classification is crucial for cultural relic restoration. 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