Research on Behavior Recognition of Dairy Goat Based on Multi-model Fusion

Abstract

In order to accurately identify the behavior of dairy goats in the image, a multi-model fusion convolutional neural network (CNN) method based on the image of dairy goats is proposed. At first, the AlexNet, ResNet50 and Vgg16 models are trained respectively, and the best recognition results of each model are obtained. Then, the attention weight of each model is calculated by feature stitching and other operations. Finally,The feature information of AlexNet, ResNet50 and Vgg16 is combined with attention mechanism to re-weight,and the parameters of the fused multi-model convolutional neural networks are adjusted to obtain the best recognition results of fusion models. Experimental results show that compared with single model and multi-model, the ARV fusion model we proposed achieves higher recognition accuracy, and the average accuracy of each dairy goat behavior is as high as 98.50%.