Animal Sciences Commons^™

Individual Beef Cattle Identification Using Muzzle Images And Deep Learning Techniques, Guoming Li, Galen E. Erickson, Yijie Xiong

Department of Animal Science: Faculty Publications

The ability to identify individual animals has gained great interest in beef feedlots to allow for animal tracking and all applications for precision management of individuals. This study assessed the feasibility and performance of a total of 59 deep learning models in identifying individual cattle with muzzle images. The best identification accuracy was 98.7%, and the fastest processing speed was 28.3 ms/image. A dataset containing 268 US feedlot cattle and 4923 muzzle images was published along with this article. This study demonstrates the great potential of using deep learning techniques to identify individual cattle using muzzle images and to support …