Cow Rump Identification Based on Lightweight Convolutional Neural Networks

Information

卷:12

Wei Shi¹  Weizheng Shen¹  Jinyan Guo¹  Zhe Zhang¹  Shengli Kou²  Handan Hou³ 

[1] College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China;

[2] Department of Science and Technology, Northeast Agricultural University, Harbin 150030, China;

[3] School of Computer Science, Harbin Finance University, Harbin 150030, China;

关键词: cow rump identification;    smart animal husbandry;    computer vision;    convolutional neural networks;    object detection;   

DOI  :  10.3390/info12090361

来源: DOAJ

【 摘 要 】

Individual identification of dairy cows based on computer vision technology shows strong performance and practicality. Accurate identification of each dairy cow is the prerequisite of artificial intelligence technology applied in smart animal husbandry. While the rump of each dairy cow also has lots of important features, so do the back and head, which are also important for individual recognition. In this paper, we propose a non-contact cow rump identification method based on convolutional neural networks. First, the rump image sequences of the cows while feeding were collected. Then, an object detection model was applied to detect the cow rump object in each frame of image. Finally, a fine-tuned convolutional neural network model was trained to identify cow rumps. An image dataset containing 195 different cows was created to validate the proposed method. The method achieved an identification accuracy of 99.76%, which showed a better performance compared to other related methods and a good potential in the actual production environment of cow husbandry, and the model is light enough to be deployed in an edge-computing device.

【 授权许可】

Unknown