Improving Swine Welfare and Production through Instance Segmentation-based Computer Vision and Machine Learning

This thesis presents a computer-vision framework for monitoring group-housed pigs, pairing Deep-Learning-based Computer Vision with traditional Machine Learning to detect mounting behaviour and estimate live body weight from overhead video in barns. It also shows how validation design shapes reported accuracy, guiding how such systems should be evaluated.