Universal Bovine Identification via Depth Data and Deep Metric Learning

arXiv:2404.00172v1 Announce Type: cross
Abstract: This paper proposes and evaluates, for the first time, a top-down (dorsal view), depth-only deep learning system for accurately identifying individual cattle and provides associated code, datasets, and training weights for immediate reproducibility. An increase in herd size skews the cow-to-human ratio at the farm and makes the manual monitoring of individuals more challenging. Therefore, real-time cattle identification is essential for the farms and a crucial step towards precision livestock farming. Underpinned by our previous …

abstract arxiv code cs.ai cs.cv cs.lg data datasets deep learning human identification paper reproducibility training type universal via view