SOG-YOLO: An Infrared Road Scene Small Object Detection Model

SOG-YOLO: An Infrared Road Scene Small Object Detection Model | 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 SOG-YOLO: An Infrared Road Scene Small Object Detection Model Ende Peng, Qing Ai, Ziqiang Li, Tao Han, Shaoyu Mao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6454914/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 22 You are reading this latest preprint version Abstract In intelligent transportation and safety monitoring, infrared road object detection technology holds significant value due to its low-light environmental advantages. However, inherent limitations such as low image resolution and blurred textures cause severe feature information loss and insufficient small-object detection accuracy in existing algorithms. This study proposes an infrared road small-object detection model integrating super-resolution reconstruction with improved YOLOv10n called SOG-YOLO. The Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) is employed to reconstruct image details. A Dynamic Generalized Efficient Layer Aggregation Network (D-GELAN) enhances feature fusion, combined with Omni-Dimensional Dynamic Convolution (OD-Conv) for adaptive feature extraction. A neck structure called DD-PAN is designed to capture weak small-object features with low computational cost. Experiments on two infrared road datasets demonstrate that SOG-YOLO achieves recall improvements of 7.4% and 10.4% respectively compared to baseline models, with mAP50 increasing by 7.4% and 10.3% correspondingly. This provides an efficient solution for infrared road object detection. Infrared road images Image super-resolution reconstruction YOLOv10 Small-size object detection Full Text Additional Declarations No competing interests reported. Supplementary Files PaperIllustrationSOGYOLOAnInfraredRoadSceneSmallObjectDetectionModel.zip Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Jun, 2025 Reviews received at journal 18 Jun, 2025 Reviews received at journal 17 Jun, 2025 Reviews received at journal 17 Jun, 2025 Reviews received at journal 16 Jun, 2025 Reviewers agreed at journal 13 Jun, 2025 Reviews received at journal 10 Jun, 2025 Reviewers agreed at journal 09 Jun, 2025 Reviewers agreed at journal 09 Jun, 2025 Reviewers agreed at journal 07 Jun, 2025 Reviewers agreed at journal 07 Jun, 2025 Reviewers agreed at journal 07 Jun, 2025 Reviewers agreed at journal 07 Jun, 2025 Reviewers agreed at journal 06 Jun, 2025 Reviewers agreed at journal 06 Jun, 2025 Reviewers agreed at journal 05 Jun, 2025 Reviewers agreed at journal 05 Jun, 2025 Reviewers agreed at journal 05 Jun, 2025 Reviewers invited by journal 05 Jun, 2025 Editor assigned by journal 05 Jun, 2025 Submission checks completed at journal 17 Apr, 2025 First submitted to journal 15 Apr, 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. 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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-6454914","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":468032819,"identity":"6f2587b7-c439-4368-b945-3012909a23a9","order_by":0,"name":"Ende Peng","email":"","orcid":"","institution":"Hubei Normal University","correspondingAuthor":false,"prefix":"","firstName":"Ende","middleName":"","lastName":"Peng","suffix":""},{"id":468032820,"identity":"ce9b2cc7-4868-472b-abb8-2eea00c022b1","order_by":1,"name":"Qing 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