Individual identification of dairy cows based on comprehensive face and trunk information
In order to increase the low accuracy in identifying individual dairy cows based on single information,a method based on the comprehensive information of the dairy cow's face and trunk was proposed.On the basis of the Mask R-CNN model,the Convolutional block attention module was introduced into the output stage of Mask R-CNN's ResNet50 feature extraction network,which could enhance the identity information of dairy cows in image channel and space.Based on different parts of dairy cows,this paper used the improved Mask R-CNN model to carry out relevant experiments with the information of dairy cow face,trunk and comprehensive information of dairy cow face and trunk.The experimental results showed that the comprehensive information of dairy cow face and trunk increased the recognition accuracy of the original Mask R-CNN model that was 2.3%to 3.7%higher than the face or trunk single information.The accuracy rate was 93.63%and mAP was 92.16%of improved Mask R-CNN model on the self-built data set of dairy cows,which has been increased by 2.92%and 2.63%respectively compared with the original Mask R-CNN model.The method in this paper could identify individual dairy cows in farms and provide technical support for precise breeding of dairy cows.
dairy cowscow face and trunkindividual identificationMask R-CNNconvolutional block attention
NETL
NSTL
万方数据
