Lameness Detection
Lameness detection in dairy cows aims to develop automated systems for early and objective identification of this costly and welfare-compromising condition. Current research focuses on leveraging computer vision, employing deep learning models (including pose estimation techniques) to analyze video and sensor data (e.g., from wearable devices) to extract gait characteristics indicative of lameness, such as stride length and posture. Improved accuracy is achieved by incorporating multiple locomotion traits and by using image segmentation to enhance feature extraction from video. These advancements offer the potential for more efficient and accurate lameness diagnosis, leading to improved animal welfare and reduced economic losses for farmers.