Enhanced Underwater Object Detection via Multi-Scale Attention and Adaptive Feature Fusion

Enhanced Underwater Object Detection via Multi-Scale Attention and Adaptive Feature Fusion | 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 Enhanced Underwater Object Detection via Multi-Scale Attention and Adaptive Feature Fusion HuiChen, YongjieYu, TaoFu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7938944/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 Underwater target detection faces challenges due to poor image quality, multi-scale variations, and occlusion. This study introduces a novel model integrating multi-scale attention and adaptive feature fusion to enhance detection accuracy. Leveraging the DEIM framework, we propose a Multi-Scale Attention Block (MSAB) for improved feature extraction across scales, a Lightweight Sparse Self-Attention Block (LSSA) for noise suppression, an Adaptive Weighted Downsampling Block (AWDS) for information preservation, and a Context-Guided Feature Fusion Module (CGFM) for intelligent feature integration. Experimental results on URPC and DUO datasets demonstrate significant improvements in AP, AP50, and AP75 metrics compared to the baseline model DEIM, with gains of 3.2%, 3.3%, and 3.4% on URPC, and 3.9%, 3.6%, and 4.7% on DUO, respectively. These findings underscore the effectiveness of our approach in addressing the complexities of underwater environments. https://github.com/EUOD/MSAuod. Artificial Intelligence and Machine Learning Underwater target detection multi-scale attention adaptive feature fusion sparse attention mechanism deep learning Full Text Additional Declarations The authors declare potential competing interests as follows: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 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-7938944","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":534409068,"identity":"7814361e-3446-4119-bcfd-b1e4d3f732cb","order_by":0,"name":"HuiChen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACAwbGBmYgLQflMxOvxRiIGRuI1AJRlthAtBZzieTGzwUVd9L7Z6Q/f8BQYZ3YwH72AF4tljMSm6VnnHmWO+NGjmEDw5n0xAaevAT8DruR2MbM23Y4t+FGDmMDY9vhxAYJHgMitPw7nC5/I/1hA+M/orU0HE4wuJFg2MDYQIyWMw+bpXmOHTbceOaN4YyEY+nGbTw5BLQcT3/4mafmsLzc8fQHHz7UWMv2s5/BrwUVJAAxGwnqR8EoGAWjYBTgAADipUkIOJOQ/QAAAABJRU5ErkJggg==","orcid":"","institution":"Anhui University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"","middleName":"","lastName":"HuiChen","suffix":""},{"id":534409069,"identity":"aaaf957c-4d38-4f91-90f2-2361c20cdd79","order_by":1,"name":"YongjieYu","email":"","orcid":"","institution":"Anhui University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"","lastName":"YongjieYu","suffix":""},{"id":534409070,"identity":"3c48dc6f-0ada-4073-b0a6-886bde249f86","order_by":2,"name":"TaoFu","email":"","orcid":"","institution":"Anhui University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"","lastName":"TaoFu","suffix":""}],"badges":[],"createdAt":"2025-10-24 10:32:57","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7938944/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7938944/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94449660,"identity":"3199edd5-cfa0-4348-9f80-adad8a6f875e","added_by":"auto","created_at":"2025-10-27 14:38:38","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":30215359,"visible":true,"origin":"","legend":"","description":"","filename":"Underwatertargetdetectionmethodintegratingmulti.docx","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/ab79b4c26a8cafb56cfa098a.docx"},{"id":94449935,"identity":"d431c746-157c-4707-bcc8-318a3d5731d8","added_by":"auto","created_at":"2025-10-27 14:38:51","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs7938944.json","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/6d654d0045afcb530cb2b8f7.json"},{"id":94449822,"identity":"f0e0be3b-9ba5-4aae-af07-6ae72ec3336f","added_by":"auto","created_at":"2025-10-27 14:38:45","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179791,"visible":true,"origin":"","legend":"","description":"","filename":"rs79389440enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/7dba9cf5be3c4bd7d9d3ab4d.xml"},{"id":94449840,"identity":"a9c08c65-e246-46b6-8e23-1f5a0e73e054","added_by":"auto","created_at":"2025-10-27 14:38:47","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8763377,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/eadcc26579eaa45a6c2e2be7.png"},{"id":94450191,"identity":"3b8d18db-b762-48bf-ba44-e41872bab186","added_by":"auto","created_at":"2025-10-27 14:39:03","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2905265,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/3e10579f3f32b0e20aa9ff55.png"},{"id":94450799,"identity":"f9a6700a-68f1-4727-841a-e4fb7e12b778","added_by":"auto","created_at":"2025-10-27 14:39:36","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2696826,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/46dad430b1621f7bd77583bb.png"},{"id":94450638,"identity":"e9e55b4e-4b6f-4ee2-a6e3-4d11405bd751","added_by":"auto","created_at":"2025-10-27 14:39:26","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":63927,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/697a352f7a9063182ea28fd8.png"},{"id":94450687,"identity":"164eb821-b6c8-4148-b2c0-ce0af8f26d7e","added_by":"auto","created_at":"2025-10-27 14:39:31","extension":"jpeg","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":75970,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage13.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/cf80b9e4a49a53a7cd15650d.jpeg"},{"id":94449658,"identity":"f00b39d5-6af3-4c5b-bf8a-fa16bd6ee7db","added_by":"auto","created_at":"2025-10-27 14:38:38","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":27790,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage14.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/77c512b0ec6e3742cd8e7bdc.jpeg"},{"id":94450021,"identity":"49f66a7f-4016-4829-b27a-1651224c1d70","added_by":"auto","created_at":"2025-10-27 14:38:56","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1700031,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/07a694a22db6d7f4b3fdeed9.png"},{"id":94450148,"identity":"ab04771f-d5d2-468b-a869-5cefc6d1fa79","added_by":"auto","created_at":"2025-10-27 14:39:00","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":742559,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/e2ce95da3dccc061da2f0a16.png"},{"id":94449132,"identity":"9bc4abf9-1dfd-4f79-a61d-2573d9da1094","added_by":"auto","created_at":"2025-10-27 14:37:56","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1994967,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/daa277b21ac1b94f27e58791.png"},{"id":94450005,"identity":"b4035e84-df22-4469-af39-897afb0e62e8","added_by":"auto","created_at":"2025-10-27 14:38:55","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4587183,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/fe404342c07129822af9580f.png"},{"id":94450697,"identity":"8611f2d2-99ca-4a28-b99e-574d4b374c20","added_by":"auto","created_at":"2025-10-27 14:39:32","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1000347,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/d5a6dbb6ad4673cf775729ba.png"},{"id":94450376,"identity":"04b59919-fe39-4eb6-86b5-80c15fbb30cd","added_by":"auto","created_at":"2025-10-27 14:39:14","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2257591,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/8b8b31cdb1714b3b87ff4548.png"},{"id":94449847,"identity":"bdba8e9d-d74b-4bcb-ac20-aae28b0a585d","added_by":"auto","created_at":"2025-10-27 14:38:48","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1806133,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/44f09cedc38b761e0c1364f7.png"},{"id":94449661,"identity":"eb45d20f-69af-47f7-9d4d-5f7e8052c0e3","added_by":"auto","created_at":"2025-10-27 14:38:39","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1400624,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/ab7afbc4db93374bbe091dc1.png"},{"id":94449949,"identity":"313a22ba-a654-40d0-88ce-e790cbb0b479","added_by":"auto","created_at":"2025-10-27 14:38:53","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":688,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/7c6daf3e03aaa5f33fa00f6c.png"},{"id":94450801,"identity":"0b826701-9493-45b9-a84f-ec836042f124","added_by":"auto","created_at":"2025-10-27 14:39:36","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":321790,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/bce7c2951506ba55b9abcd6c.png"},{"id":94449664,"identity":"b692a09f-8011-464e-9f5a-db24b567e0ae","added_by":"auto","created_at":"2025-10-27 14:38:39","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":222601,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/e27d8b8cb1efb5d9541f3e15.png"},{"id":94449956,"identity":"53f1edbb-291c-49c8-b532-4939b0d68cc0","added_by":"auto","created_at":"2025-10-27 14:38:53","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14409,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/c6a1897e02d89f0bf23b3910.png"},{"id":94450042,"identity":"53b8f7ce-d005-4870-8cd9-ef6068364cb4","added_by":"auto","created_at":"2025-10-27 14:38:56","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107530,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/f386c42e8dbcd8804764c1d7.png"},{"id":94450666,"identity":"974e2562-c101-44ce-906e-0416a4a40be2","added_by":"auto","created_at":"2025-10-27 14:39:30","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37852,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/ca67f3a0b9603610645b45f9.png"},{"id":94450420,"identity":"42c7526e-7e39-43fa-9bbe-456429099a71","added_by":"auto","created_at":"2025-10-27 14:39:16","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":698742,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/7543af63df95cc9df8cf03a7.png"},{"id":94450356,"identity":"ecbd5f2b-b2e9-488e-85d5-f8499d4dc89f","added_by":"auto","created_at":"2025-10-27 14:39:12","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":285340,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/6a11cd03bedb8c5eacfc9c7b.png"},{"id":94449844,"identity":"8fdc80ba-0d88-4d8c-bb9a-d7107852d4c1","added_by":"auto","created_at":"2025-10-27 14:38:47","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":720089,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/d3cbf5f1c9085415d385b66f.png"},{"id":94489913,"identity":"593af058-bbbd-4223-ab15-58d7427b5b87","added_by":"auto","created_at":"2025-10-27 17:06:30","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1524472,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/cc1af3dafd3f9958399d600e.png"},{"id":94449662,"identity":"82f7c8c3-ec49-41fa-bd5f-76c489858c7d","added_by":"auto","created_at":"2025-10-27 14:38:39","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":378661,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/03f4583ace8e29f5925827e4.png"},{"id":94450192,"identity":"073aa48f-f7a4-4718-8d3d-583a88fbbdac","added_by":"auto","created_at":"2025-10-27 14:39:03","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":641493,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/1a7642caeb3bf3442f83f15c.png"},{"id":94450201,"identity":"a70db742-7774-4e60-866c-1d105359984c","added_by":"auto","created_at":"2025-10-27 14:39:03","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":523855,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/e063260924b9af9768df36bc.png"},{"id":94450889,"identity":"493c29e8-a73a-452f-89bc-b722cfbbdd44","added_by":"auto","created_at":"2025-10-27 14:39:39","extension":"xml","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":178801,"visible":true,"origin":"","legend":"","description":"","filename":"rs79389440structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/703a88650fc24745520b4ac5.xml"},{"id":94449957,"identity":"1b21f551-5a60-49ea-bff6-842376765dc1","added_by":"auto","created_at":"2025-10-27 14:38:53","extension":"html","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":200359,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1/5d0e8bd3b244bb79e9879f8d.html"},{"id":94491287,"identity":"e7685453-004f-4300-a198-e60a7f84ce58","added_by":"auto","created_at":"2025-10-27 17:24:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1322295,"visible":true,"origin":"","legend":"","description":"","filename":"Underwatertargetdetectionmethodintegratingmulti.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7938944/v1_covered_d2fcc9fd-178b-46cc-ad11-fa12afe45db6.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","formattedTitle":"\u003cp\u003eEnhanced Underwater Object Detection via Multi-Scale Attention and Adaptive Feature Fusion\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"National Natural Science Foundation of China","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":"Underwater target detection, multi-scale attention, adaptive feature fusion, sparse attention mechanism, deep learning","lastPublishedDoi":"10.21203/rs.3.rs-7938944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7938944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderwater target detection faces challenges due to poor image quality, multi-scale variations, and occlusion. This study introduces a novel model integrating multi-scale attention and adaptive feature fusion to enhance detection accuracy. Leveraging the DEIM framework, we propose a Multi-Scale Attention Block (MSAB) for improved feature extraction across scales, a Lightweight Sparse Self-Attention Block (LSSA) for noise suppression, an Adaptive Weighted Downsampling Block (AWDS) for information preservation, and a Context-Guided Feature Fusion Module (CGFM) for intelligent feature integration. Experimental results on URPC and DUO datasets demonstrate significant improvements in AP, AP50, and AP75 metrics compared to the baseline model DEIM, with gains of 3.2%, 3.3%, and 3.4% on URPC, and 3.9%, 3.6%, and 4.7% on DUO, respectively. These findings underscore the effectiveness of our approach in addressing the complexities of underwater environments. https://github.com/EUOD/MSAuod.\u003c/p\u003e","manuscriptTitle":"Enhanced Underwater Object Detection via Multi-Scale Attention and Adaptive Feature Fusion","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-27 11:30:08","doi":"10.21203/rs.3.rs-7938944/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"73024bc6-e551-4a31-911e-bc6fbabdcd4d","owner":[],"postedDate":"October 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56822355,"name":"Artificial Intelligence and Machine Learning"}],"tags":[],"updatedAt":"2025-12-28T10:53:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-27 11:30:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7938944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7938944","identity":"rs-7938944","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}