LEN-YOLO: A Lightweight Remote Sensing Small Aircraft ObjectDetection Model for Satellite On-Orbit Detection

LEN-YOLO: A Lightweight Remote Sensing Small Aircraft ObjectDetection Model for Satellite On-Orbit Detection | 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 LEN-YOLO: A Lightweight Remote Sensing Small Aircraft ObjectDetection Model for Satellite On-Orbit Detection Jian Wu, Fanyu Zhao, Zhonghe Jin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4836110/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Dec, 2024 Read the published version in Journal of Real-Time Image Processing → Version 1 posted 14 You are reading this latest preprint version Abstract Due to the complex backgrounds of remote sens2 ing images and the small size of aircraft targets, the results of 3 commonly used detection algorithms in small aircraft target 4 detection are not satisfactory. Moreover, the prevalent deep 5 learning algorithms are generally too cumbersome to adapt 6 to the resource-constrained satellite platforms. To improve 7 detection accuracy while maintaining model simplicity for 8 satellite on-orbit small aircraft detection, we develop an im9 proved algorithm based on YOLOv5, called LEN-YOLO. 10 Firstly, we adopt the EIoU Loss for target localization, en11 abling the network to effectively focus on small aircraft tar12 gets. Second, a Lite backbone is designed by discarding high 13 semantic information, using low semantic feature maps to 14 detect small targets. Finally, we propose a BSG-FPN struc15 ture to fuse feature maps of different scales to increase de16 tailed information. Experimental results on RSOD and DIOR 17 datasets demonstrate compared to the baseline YOLOv5, 18 LEN-YOLO achieves an increase of 5.1% and 4.2% in APs 19 respectively. Notably, parameters are reduced by 78.3% and 20 floating-point operations by 33.2%. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Dec, 2024 Read the published version in Journal of Real-Time Image Processing → Version 1 posted Editorial decision: Revision requested 22 Sep, 2024 Reviews received at journal 18 Sep, 2024 Reviews received at journal 14 Sep, 2024 Reviews received at journal 14 Sep, 2024 Reviews received at journal 11 Sep, 2024 Reviewers agreed at journal 09 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers invited by journal 02 Sep, 2024 Editor assigned by journal 01 Aug, 2024 Submission checks completed at journal 01 Aug, 2024 First submitted to journal 31 Jul, 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. 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-4836110","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338174250,"identity":"547e0541-2ecc-4581-86a5-91157a5060ba","order_by":0,"name":"Jian Wu","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Wu","suffix":""},{"id":338174251,"identity":"a52f0c97-1a28-484b-8314-777189b3b53b","order_by":1,"name":"Fanyu Zhao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYNCCAhBxgPFBQkUNsVoMwFqYDR6cOUaSFgY2yYctzIQV87f3PnxcYGCXJ994xqwisYENKNKdgFeLxJnjxsYzDJKLGRvOmN1I3CEDFDm7Ab81N9LYpHkMmBObGUBazrAxGEjk4tcif/8ZSEt9YhtQS0FiGzNhLQY32EBaDif2ALUwEKXF8EwaM9AvxxNnMBwrlkg4c4yHoF/kjh9jfFxQUZ04f8bhjR9/VNTIAcOQgPeBABIXEgfAFA9B5Qgt/A1EKR4Fo2AUjIIRCAA8OEblHfAorQAAAABJRU5ErkJggg==","orcid":"","institution":"Zhejiang University","correspondingAuthor":true,"prefix":"","firstName":"Fanyu","middleName":"","lastName":"Zhao","suffix":""},{"id":338174257,"identity":"a606d3e0-8a73-400a-96e0-8b094092c215","order_by":2,"name":"Zhonghe Jin","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Zhonghe","middleName":"","lastName":"Jin","suffix":""}],"badges":[],"createdAt":"2024-07-31 13:55:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4836110/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4836110/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11554-024-01601-x","type":"published","date":"2024-12-19T15:58:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":72201936,"identity":"51fd7ea8-76b0-431e-a37f-650ff5375bf4","added_by":"auto","created_at":"2024-12-23 16:12:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4606203,"visible":true,"origin":"","legend":"","description":"","filename":"LENYOLOJRTIP1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4836110/v1_covered_6f95990b-aa23-4ac9-ad41-f1416b265a5c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"LEN-YOLO: A Lightweight Remote Sensing Small Aircraft ObjectDetection Model for Satellite On-Orbit Detection","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":"journal-of-real-time-image-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rtip","sideBox":"Learn more about [Journal of Real-Time Image Processing](http://link.springer.com/journal/11554)","snPcode":"11554","submissionUrl":"https://submission.nature.com/new-submission/11554/3","title":"Journal of Real-Time Image Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4836110/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4836110/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDue to the complex backgrounds of remote sens2 ing images and the small size of aircraft targets, the results of 3 commonly used detection algorithms in small aircraft target 4 detection are not satisfactory. Moreover, the prevalent deep 5 learning algorithms are generally too cumbersome to adapt 6 to the resource-constrained satellite platforms. To improve 7 detection accuracy while maintaining model simplicity for 8 satellite on-orbit small aircraft detection, we develop an im9 proved algorithm based on YOLOv5, called LEN-YOLO. 10 Firstly, we adopt the EIoU Loss for target localization, en11 abling the network to effectively focus on small aircraft tar12 gets. Second, a Lite backbone is designed by discarding high 13 semantic information, using low semantic feature maps to 14 detect small targets. Finally, we propose a BSG-FPN struc15 ture to fuse feature maps of different scales to increase de16 tailed information. Experimental results on RSOD and DIOR 17 datasets demonstrate compared to the baseline YOLOv5, 18 LEN-YOLO achieves an increase of 5.1% and 4.2% in APs 19 respectively. Notably, parameters are reduced by 78.3% and 20 floating-point operations by 33.2%.\u003c/p\u003e","manuscriptTitle":"LEN-YOLO: A Lightweight Remote Sensing Small Aircraft ObjectDetection Model for Satellite On-Orbit Detection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-22 19:32:58","doi":"10.21203/rs.3.rs-4836110/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-22T13:38:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-18T04:22:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-14T17:26:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-14T05:27:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-11T09:29:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280982114568155014846960532049120170792","date":"2024-09-09T13:25:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"30066568958293251978139110160468715869","date":"2024-09-02T19:48:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59556436594138175692209729173153386822","date":"2024-09-02T15:55:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37379321853108233092713960668642806126","date":"2024-09-02T15:31:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291261410406568904526099184070693843736","date":"2024-09-02T12:52:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-02T11:56:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-01T12:41:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-01T12:39:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Real-Time Image Processing","date":"2024-07-31T13:54:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-real-time-image-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rtip","sideBox":"Learn more about [Journal of Real-Time Image Processing](http://link.springer.com/journal/11554)","snPcode":"11554","submissionUrl":"https://submission.nature.com/new-submission/11554/3","title":"Journal of Real-Time Image Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"629413f7-e6b3-40f3-a010-d55b74bbf5bc","owner":[],"postedDate":"August 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:04:48+00:00","versionOfRecord":{"articleIdentity":"rs-4836110","link":"https://doi.org/10.1007/s11554-024-01601-x","journal":{"identity":"journal-of-real-time-image-processing","isVorOnly":false,"title":"Journal of Real-Time Image Processing"},"publishedOn":"2024-12-19 15:58:17","publishedOnDateReadable":"December 19th, 2024"},"versionCreatedAt":"2024-08-22 19:32:58","video":"","vorDoi":"10.1007/s11554-024-01601-x","vorDoiUrl":"https://doi.org/10.1007/s11554-024-01601-x","workflowStages":[]},"version":"v1","identity":"rs-4836110","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4836110","identity":"rs-4836110","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}