Cattle Identification

Cattle identification research focuses on developing accurate and efficient methods for individually recognizing cattle, primarily to improve livestock management and traceability within precision farming and financial applications. Current research heavily utilizes deep learning, employing architectures like YOLO, ResNet, and FaceNet, often leveraging unique bovine features such as muzzle prints or overall body shape from images or depth data. These advancements offer improved accuracy in individual animal identification compared to traditional methods, impacting areas like livestock insurance, biosecurity, and sustainable finance by enabling better monitoring and risk assessment.