农业机械学报2024，Vol.55Issue(6)：246-253,8.DOI:10.6041/j.issn.1000-1298.2024.06.026
基于运动特征提取和2D卷积的鱼类摄食行为识别研究
Recognition of Feeding Behavior of Fish Based on Motion Feature Extraction and 2D Convolution
摘要
Abstract
In order to promote the intelligence of fishery equipment,video streaming-based fish feeding behaviour recognition has received extensive attention in recent years.The model of traditional recognition methods based on video streaming is too complex to be realized on edge computing devices.To address this problem,a lightweight 2D convolutional motion feature extraction network,Motion-EfficientNetV2,was proposed which can effectively recognize fish feeding behaviour by using video streams as input.The proposed model used EfficientNetV2 as the backbone network,constructed the motion feature extraction module Motion based on TEA and ECANet,and embeded the Motion module into each Fused-MBConv module of EfficientNetV2,in order to give EfficientNetV2 the ability to extract motion features.The MBConv in the EfficientNetV2 network was also improved by using ECANet to enhance its channel feature extraction capability.Null convolution was used in Motion-EfficientNetV2 to expand the receptive field and improve the wide-range feature extraction capability.The experimental results showed that after introducing the designed Motion module and a series of improvements,the number of parameters and FLOPs of Motion-EfficientNetV2 was 9 × 106 and 1.31 × 1010,respectively,which were reduced compared with EfficientNetV2.Comparison experiments using the same dataset in the algorithmic models of TSN-ResNet50,TSN-EfficientNetV2,C3D,and R3D,respectively,showed that the present algorithm achieved an accuracy of 93.97％while the number of parameters and FLOPs were lower than the rest of the models.Therefore,the model proposed can effectively identify fish feeding behavior and guide aquaculturists to develop fish feeding strategies.关键词
鱼类摄食行为/运动特征/深度学习/卷积神经网络/轻量化/EfficientNetV2Key words
feeding behavior of fish/motion feature/deep learning/convolutional neural network/lightweight/EfficientNetV2分类
农业科技引用本文复制引用
张铮,沈彦兵,张泽扬..基于运动特征提取和2D卷积的鱼类摄食行为识别研究[J].农业机械学报,2024,55(6):246-253,8.基金项目
上海市崇明区农业科创项目(2021CNKC-05-06)、国家重点研发计划项目(2023YFD2401304)和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) （2021CNKC-05-06）
