基于改进YOLOv8s模型的河蟹幼苗雌雄检测方法

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GenderDetectionMethodforCrabsSeedlingsBasedonEnhancedYOLOv8sModel

LI Xian，MA Ming，HUZhi-gangetal（ScholofMchanicalEnginering，WuhanLightIndustry University，Wuhan，Hubei0496） AbstractInespsetoteproblmofuceardierentiatiobetwenalesndealesuringthsdingsageofiverabfi cientaccuracyinmanalclasificatioofaleandfemaleinvrabsdling.Tisticleproposametdfordetetigtederf rivercrabsedingasedonanimprovedOLO8odel.eiprovementmetodisasflow：fistlyeplacethfourthlayeCfodule inthebackboneetworkwithCfGAM（globalatentionchanism，GAM）module，djust hewightoffatureiforatioandducete lossoffeaturefoatiodingtassidlyplacealdarysfciiheU（edtef sequentialevideceforintersetooveruiov）boundysfuctiotohaethancroxualityduringtepreditoprosd improvetheodel’sneralzatiobilityfiallearestigoriteplatiousaplingtodineadetwokisplacdih CARAFE（contentawarereassemblyoffeatures）upsaplingmetodichivesteodellargereceptivefeldndimproesitsfo ance.The experimental results sow that the accuracy，recall，and average precision of the improved model are98. 4% ，91. 1% ，and 96. 1% ， respctivelyhcre3..d2.9prenaeoterthaeigialodel.eulsicatethaslityoflnga chine vision to the clasification of male and female crab seedlings and the effectiveness of the improved method.

Key wordsCrab seedlings；YOLOv8s；WIoU；GAM；CRAFF

近年来，随着人工智能技术的不断进步，越来越多的行业为了追求高质量发展，将传统技术与人工智能技术进行结合[1-2]。（剩余8718字）