华南农业大学学报2024，Vol.45Issue(5)：754-763,10.DOI:10.7671/j.issn.1001-411X.202404003
基于Swin-Unet的奶牛饲料消耗状态监测方法
Feed consumption status monitoring method of dairy cows based on Swin-Unet
摘要
Abstract
[Objective]In view of the characteristics of the feed area in the monitoring image,which has a long structure,fuzzy boundaries,as well as complex and changeable shapes and sizes,the aim of this study was to more accurately segment the feed residual area and consumption area,and achieve the purpose of accurately monitoring the feed consumption status.[Method]This study proposed a semantic segmentation model based on Swin-Unet,which applied ConvNeXt block at the beginning of the Swin Transformer block to enhance the model's ability of encoding feature information to provide better feature representation.The model used depth-wise convolution to replace linear attention projection to provide local spatial context information.At the same time,a novel wide receptive field module was proposed to replace the multi-layer perceptron to enrich multi-scale spatial context information.In addition,at the beginning of the encoder,the linear embedding layer was replaced with a convolutional embedding layer,which introduces more spatial context information between and within patches by compressing features in stages.Finally,a multi-scale input strategy,a deep supervision strategy and a feature fusion module were introduced to strengthen feature fusion.[Result]The mean intersection over union,accuracy,F1-score and operation speed of the proposed method were 86.46%,98.60%,92.29%and 23 frames/s respectively,which were 4.36,2.90,0.65 percentage points and 15%higher than those of Swin-Unet.[Conclusion]It is feasible to apply the method based on image semantic segmentation to the automatic monitoring of feed consumption status.This method effectively improves the segmentation accuracy and computing efficiency by introducing convolution into Swin-Unet,which is of great significance for improving production management efficiency.关键词
饲料消耗/自动监测/语义分割/Swin Transformer/奶牛/深度卷积Key words
Feed consumption/Automatic monitoring/Semantic segmentation/Swin Transformer/Dairy cow/Deep convolution分类
农业科技引用本文复制引用
张博,罗维平..基于Swin-Unet的奶牛饲料消耗状态监测方法[J].华南农业大学学报,2024,45(5):754-763,10.基金项目
国家自然科学基金(62103309) （62103309）
湖北省数字化纺织装备重点实验室开放课题(DTL2022001) （DTL2022001）
