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University of Bristol
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Simple aggregation of predictions outperforms complex models in detecting leprosy in wild chimpanzees, highlighting the importance of data handling in wildlife health monitoring.
The PanAf-SBR dataset reveals that fine-grained social behaviour recognition in wild great apes can be significantly improved through targeted cross-dataset pre-training.
TraMP-LLaMA not only predicts severity scores but also generates interpretable reports from facial motion cues, bridging a critical gap in facial expression assessment.
Depth accuracy varies dramatically across cameras, with biases ranging from 50 mm to over 1400 mm, highlighting the critical need for informed camera selection in healthcare monitoring.
