华南农业大学学报2025，Vol.46Issue(4)：538-548,11.DOI:10.7671/j.issn.1001-411X.202410002
基于视觉与水质特征融合的鱼类摄食行为识别模型
Fish feeding behavior recognition model based on the fusion of visual and water quality features
摘要
Abstract
[Objective]To improve the accuracy of fish feeding behavior recognition in industrial aquaculture environment.[Method]A fish feeding behavior recognition model was proposed based on the fusion of visual and water quality features,namely MC-ConvNeXtV2.To better capture the global features of different aggregation levels and the detailed features of feeding behavior,a context-aware local attention mechanism(Cloatt)was introduced in each convolution stage of ConvNeXtV2-T.To improve the behavior recognition performance of the model in high-density aquaculture,a multimodal feature fusion module(MFFM)was designed to achieve adaptive fusion of visual features and dissolve oxygen,temperature,and pH of water quality features.The model test was conducted in a Micropterus salmoides culture factory with a culture density of 160 fish/m3.[Result]The test results showed that for the task of four feeding behaviors classification of fish school,the recognition accuracy,precision and recall of MC-ConvNeXtV2 model were 96.89%,96.34%,and 96.59%,respectively.Compared with ConvNeXtV2-T,these indicators increased by 3.11,2.42,and 2.72 percentage points,respectively.[Conclusion]The proposed fish feeding behavior recognition model offers a new approach for intelligent aquaculture management.关键词
水产养殖/鱼类摄食行为/多模态/ConvNeXtV2Key words
Aquaculture/Fish feeding behavior/Multimodal/ConvNeXtV2分类
农业科技引用本文复制引用
张铮,邹博胜..基于视觉与水质特征融合的鱼类摄食行为识别模型[J].华南农业大学学报,2025,46(4):538-548,11.基金项目
上海市农业科技创新项目(沪农科I2023006) （沪农科I2023006）
上海市水产动物良种创制与绿色养殖协同创新中心项目(2021科技02-12) （2021科技02-12）
