渔业现代化2026，Vol.53Issue(1)：1-14,14.DOI:10.26958/j.cnki.1007-9580.2026.01.001
计算机视觉在水产养殖中的应用现状及展望
Applications and future prospects of computer vision in aquaculture
摘要
Abstract
To systematically review the application of computer vision in the field of aquaculture,this paper provides an in-depth analysis of its current implementations and challenges across various stages of the farming process,while also offering insights into future development trends.The aim is to provide theoretical support and technical references for the intelligent transformation and upgrading of aquaculture.This study focuses on the specific application pathways and performance of visual recognition algorithms-such as convolutional neural networks and the YOLO series in aquaculture.It also elaborates on the advantages and development potential of multi-modal fusion algorithms in integrating visual images,acoustic signals,and water quality monitoring data.Existing research demonstrates that computer vision technologies can significantly enhance the precision management and production efficiency of aquaculture operations.Multi-modal fusion algorithms,in particular,have shown outstanding performance in key tasks such as fish behavior recognition and quantitative analysis of feeding intensity.However,computer vision algorithms still face challenges in practical applications,including poor image quality caused by complex underwater imaging environments and increased recognition difficulty due to diverse fish behavior patterns.Looking ahead,with the optimization of deep learning algorithms,further application of multi-modal fusion technology,and cross-disciplinary integration with technologies such as the Internet of Things and aquaculture robotics,computer vision is expected to provide critical technical support for the efficient,precise,and sustainable development of aquaculture.This will play a significant role in ensuring global aquatic product supply and food security.关键词
计算机视觉/水产养殖/算法应用/多模态融合/智能化养殖Key words
computer vision/aquaculture/algorithm application/multimodal fusion/intelligent aquaculture分类
农业科技引用本文复制引用
彭飞,宋雨龙,袁华荣,刘宏轩,付庆贺,黄立俊,张丽梅,郑阿钦..计算机视觉在水产养殖中的应用现状及展望[J].渔业现代化,2026,53(1):1-14,14.基金项目
浙江省淡水水产研究所开放课题(ZJK202506) （ZJK202506）
农业农村部海洋牧场重点实验室开放基金(KLMR-2025-06) （KLMR-2025-06）
福建省海洋生物增养殖与高值化利用重点实验室项目(2026fjscq05) （2026fjscq05）
国家自然科学基金项目(52005012) （52005012）
