Research on cherry maturity detection based on improved DS-YOLOV8

Research on cherry maturity detection based on improved DS-YOLOV8 | 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 Research on cherry maturity detection based on improved DS-YOLOV8 Song You, ChangQing Zhang, Chenchen Wang, ShaoTong Ning This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3937772/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 In order to automatically detect the maturity of cherry fruits in the natural environment 1 and realize the automatic picking of cherry fruits, three levels of cherry fruit maturity (Green ripening 2 stage, medium ripening stage, full ripening stage) were formulated according to the changes of 3 cherry fruit phenotypic characteristics in the mature stage and the company standard GH/T 1193-2021. Aiming at the problem that the difference of adjacent cherries’ maturity characteristics is not obvious and the mutual occlusion between fruits, an improved YOLO v8 model is proposed for cherry fruit maturity detection. In this method, the Dymatic Snake Convolution (DSconv) module 7 was introduced into the YOLO v8 model as the backbone feature extraction network to reduce the number of parameters of the network. At the same time, the spatial attention mechanism (including 9 CBMA and FocalModulation modules) was added to the feature fusion network to improve the feature expression ability of the network. The experimental results show that the average precision, 11 recall and average precision of the improved YOLO v8 model under the test set are 98.6%, 98.1% and 12 98.2% respectively. Compared with Faster R-CNN, YOLO v3 and YOLO v5s, the improved YOLO v8 13 model has improved by 18.7, 0.2, 0.3 and 0.1 percentage points respectively. The results show that the 14 improved YOLO v8 model can provide technical support for the automatic picking of cherries. Improve YOLOv8 Cherry maturity Object detection Spatial attention mechanism 16 Full Text Additional Declarations No competing interests reported. Supplementary Files valbatch0labels.jpg valbatch0pred.jpg trainbatch2.jpg valbatch1labels.jpg valbatch2labels.jpg valbatch2pred.jpg valbatch1pred.jpg trainbatch2.jpg valbatch0labels.jpg valbatch0pred.jpg valbatch1labels.jpg valbatch1pred.jpg valbatch2labels.jpg valbatch2pred.jpg 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-3937772","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":272148823,"identity":"1b968260-cdf8-4fd6-9fbc-03cfe1961391","order_by":0,"name":"Song You","email":"","orcid":"","institution":"Heilongjiang Bayi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Song","middleName":"","lastName":"You","suffix":""},{"id":272148824,"identity":"2004409b-89a9-4d71-9bb3-e70a561c7879","order_by":1,"name":"ChangQing Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYHACNhAhx8befoA0LcZ8PGcSSNOSOE/CwYA49fLth7c95qk5nN4mwZDA8KNiG2EtjD1p5cY8xw7ntkk3HmDsOXObsBZmCR4zaR42oBaZAwnMjG1EaGEDa/l3OJ1NIsGAOC08IC28bYcTiNciwZNWbji3L92wDRjIB4nyCyjEHrz5Zi0v395+8MGPCiK0AIEBEw+UdYAo9SAtjD+IVToKRsEoGAUjEwAANWQ2ISZhQI0AAAAASUVORK5CYII=","orcid":"","institution":"Heilongjiang Bayi Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"ChangQing","middleName":"","lastName":"Zhang","suffix":""},{"id":272148825,"identity":"b3d18d1b-14d8-42e7-a548-b9f86b393d56","order_by":2,"name":"Chenchen Wang","email":"","orcid":"","institution":"Heilongjiang Bayi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Chenchen","middleName":"","lastName":"Wang","suffix":""},{"id":272148826,"identity":"73651094-48e9-480f-8a70-1879bda7808e","order_by":3,"name":"ShaoTong Ning","email":"","orcid":"","institution":"Heilongjiang Bayi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"ShaoTong","middleName":"","lastName":"Ning","suffix":""}],"badges":[],"createdAt":"2024-02-07 19:04:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3937772/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3937772/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52417630,"identity":"93f8ffa0-3410-4720-b4ae-efc3aad1f9a4","added_by":"auto","created_at":"2024-03-11 12:09:07","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":615066,"visible":true,"origin":"","legend":"","description":"","filename":"UTF8UTF82727paper6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1_covered_08760d49-3560-4068-becc-16f3f7b84541.pdf"},{"id":50979114,"identity":"f74d6d09-b84e-436c-be6f-4cdb325d39b7","added_by":"auto","created_at":"2024-02-12 04:02:04","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":745711,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch0labels.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/954010e1c2f5caf6dc181c53.jpg"},{"id":50979115,"identity":"3cdd911e-ed9c-4b57-a695-5f1560b309a0","added_by":"auto","created_at":"2024-02-12 04:02:04","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":746812,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch0pred.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/eb3805d8c2dcdebcd251a26c.jpg"},{"id":50979116,"identity":"6f6c595b-50d6-49ab-b533-d2cb985a8b4a","added_by":"auto","created_at":"2024-02-12 04:02:04","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":882391,"visible":true,"origin":"","legend":"","description":"","filename":"trainbatch2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/9c56caeba745f08cebaacc6d.jpg"},{"id":50979285,"identity":"680b3e86-0143-4702-bc21-e60adb8ada8e","added_by":"auto","created_at":"2024-02-12 04:10:05","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":850479,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch1labels.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/491dbc3f9c63004bc530065f.jpg"},{"id":50979117,"identity":"a32e5294-17a6-442b-9d5d-45dccc6a4aa8","added_by":"auto","created_at":"2024-02-12 04:02:04","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":785363,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch2labels.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/fb3850617d9abfd3f900f287.jpg"},{"id":50979118,"identity":"24f9df58-e612-4d8d-8705-b95199972bfa","added_by":"auto","created_at":"2024-02-12 04:02:04","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":781566,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch2pred.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/c77a732b0ad21fb0f0b6e045.jpg"},{"id":50979119,"identity":"f2907768-6c13-42fa-a7b2-efef641c0c6f","added_by":"auto","created_at":"2024-02-12 04:02:04","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":851455,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch1pred.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/a953f039acce86c3d5bc572e.jpg"},{"id":50979286,"identity":"c9e73143-d47d-4709-810e-bd162e1bed69","added_by":"auto","created_at":"2024-02-12 04:10:05","extension":"jpg","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":882391,"visible":true,"origin":"","legend":"","description":"","filename":"trainbatch2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/587a2fd049790253ec4256fa.jpg"},{"id":50979120,"identity":"1ed6e623-f602-4a4e-843e-b7ffe298f68d","added_by":"auto","created_at":"2024-02-12 04:02:05","extension":"jpg","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":745711,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch0labels.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/bd9bcfc07bbe384b57442fae.jpg"},{"id":50979123,"identity":"5e72586a-0987-4925-a1d0-388caaa571ae","added_by":"auto","created_at":"2024-02-12 04:02:05","extension":"jpg","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":746812,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch0pred.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/66cca94fcfe366f6e34dabb0.jpg"},{"id":50979126,"identity":"2d17609f-c279-4de7-b4e3-a9ed975800ec","added_by":"auto","created_at":"2024-02-12 04:02:06","extension":"jpg","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":850479,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch1labels.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/8383d91b3ad93e29d4281e7d.jpg"},{"id":50979124,"identity":"c5ae9468-a3c0-4db1-ae02-799082ebe489","added_by":"auto","created_at":"2024-02-12 04:02:05","extension":"jpg","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":851455,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch1pred.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/d805cd25a08d2eaa35931d76.jpg"},{"id":50979122,"identity":"06ed11ff-80f1-4dd9-89e0-e9f442b4303d","added_by":"auto","created_at":"2024-02-12 04:02:05","extension":"jpg","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":785363,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch2labels.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/d7071d9b68e1534f815f70f0.jpg"},{"id":50979287,"identity":"06da09cc-acf9-47b4-b563-0d9ca58e5c61","added_by":"auto","created_at":"2024-02-12 04:10:06","extension":"jpg","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":781566,"visible":true,"origin":"","legend":"","description":"","filename":"valbatch2pred.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3937772/v1/c52eddb8063ce635fafa19dc.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on cherry maturity detection based on improved DS-YOLOV8","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"Improve YOLOv8, Cherry maturity, Object detection, Spatial attention mechanism 16","lastPublishedDoi":"10.21203/rs.3.rs-3937772/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3937772/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In order to automatically detect the maturity of cherry fruits in the natural environment 1 and realize the automatic picking of cherry fruits, three levels of cherry fruit maturity (Green ripening 2 stage, medium ripening stage, full ripening stage) were formulated according to the changes of 3 cherry fruit phenotypic characteristics in the mature stage and the company standard GH/T 1193-2021. Aiming at the problem that the difference of adjacent cherries’ maturity characteristics is not obvious and the mutual occlusion between fruits, an improved YOLO v8 model is proposed for cherry fruit maturity detection. In this method, the Dymatic Snake Convolution (DSconv) module 7 was introduced into the YOLO v8 model as the backbone feature extraction network to reduce the number of parameters of the network. At the same time, the spatial attention mechanism (including 9 CBMA and FocalModulation modules) was added to the feature fusion network to improve the feature expression ability of the network. The experimental results show that the average precision, 11 recall and average precision of the improved YOLO v8 model under the test set are 98.6%, 98.1% and 12 98.2% respectively. Compared with Faster R-CNN, YOLO v3 and YOLO v5s, the improved YOLO v8 13 model has improved by 18.7, 0.2, 0.3 and 0.1 percentage points respectively. The results show that the 14 improved YOLO v8 model can provide technical support for the automatic picking of cherries.","manuscriptTitle":"Research on cherry maturity detection based on improved DS-YOLOV8","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-12 04:01:58","doi":"10.21203/rs.3.rs-3937772/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":"df7d233a-d47d-4895-8d80-7dc1966289be","owner":[],"postedDate":"February 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-11T12:07:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-12 04:01:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3937772","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3937772","identity":"rs-3937772","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}