中国水产科学2025，Vol.32Issue(3)：409-419,11.DOI:10.12264/JFC2024-0352
基于YOLO的养殖鱼群全向声呐实时监测方法研究与应用
Research and application of real-time monitoring method for cultured fish based on YOLO
摘要
Abstract
To address the issues of low efficiency and insufficient accuracy in monitoring fish populations in aquaculture,this study proposes a real-time fish monitoring method based on an omnidirectional scanning sonar and the You Only Look Once(YOLO)model using tilapia(Oreochromis sp.)as the research object.The proposed method used an omnidirectional scanning sonar to collect underwater fish shoal image data.By using the YOLOv8 algorithm combined with real-time monitoring,the proposed method achieved target recognition and analysis.Euclidean distance-based spatial analysis algorithms were used to merge and exclude anomalous data points to obtain the number and spatial distribution of fish schools.Experiments were conducted to evaluate fish schools of varying sizes(50,100,150,and 200 individuals)and achieved monitoring accuracies of 93.5,94.5,89.6,and 85.8％,respectively,with an average accuracy of 90.9％.This method substantially enhanced the real-time monitoring and accuracy of fish school population assessments.This provides an efficient solution for monitoring fish schools in aquaculture towards optimizing aquaculture management,improving production efficiency,and promoting the sustainable development of ecological aquaculture.关键词
养殖鱼类/全向声呐/YOLO v8/实时监测Key words
cultured fish/omnidirectional sonar/YOLO v8/real-time monitoring分类
农业科技引用本文复制引用
孙鹏麒,胡家祯,黄小华,孙佳龙,李根,陶启友,袁太平,庞国良,胡昱..基于YOLO的养殖鱼群全向声呐实时监测方法研究与应用[J].中国水产科学,2025,32(3):409-419,11.基金项目
海南省重大科技计划项目(ZDKJ2021013) （ZDKJ2021013）
海南省重点研发项目(ZDYF2021XDNY305,ZDYF2023XDNY066) （ZDYF2021XDNY305,ZDYF2023XDNY066）
中央级公益性科研院所基本科研业务费专项(2023TD97) （2023TD97）
广州市科技计划项目(2023E04J0001) （2023E04J0001）
连云港市重点研发计划项目(22CY080,21SH038). （22CY080,21SH038）
