Thesis title: Robotic Perception for Precision Livestock Farming: Automatic lameness detectionSupervisors: Cameron CLARK , James UNDERWOOD
Lameness in dairy cows is a prevalent health issue impacting both animal welfare and economic
performance. Despite the economic and welfare cost of lameness, lameness prevalence has been shown to be severely underestimated. This is partially due to the time and expertise required to systematically recognise and score lame cows. This infrequent manual process often suffers from low consistency and subjectivity. Automatic lameness detection can potentially provide an objective, consistent lameness assessment at a higher temporal resolution, while better distinguishing lameness severity levels.