Cattle Detection

Cattle detection research focuses on developing automated systems for identifying and locating individual cattle, primarily using computer vision techniques. Current efforts concentrate on improving the accuracy and robustness of these systems, particularly addressing challenges like occlusion (hidden cattle) and variations in lighting and viewing angles, often employing deep learning architectures such as YOLO and ResNet. This work is crucial for advancing precision livestock farming, enabling improved animal management, disease monitoring, and more efficient resource allocation, ultimately impacting both farm productivity and animal welfare.