ArticleVeterinary sciences2026
Short-Term Longitudinal Biometric Identification of Cattle Using Planum Nasolabiale Images and a Two-Stage Deep Learning Framework.
Article in Veterinary sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Individual cattle identification is essential for traceability and precision livestock management, but conventional identifiers may be lost or damaged. This study evaluated a non-invasive biometric framework based on PN images. A two-stage pipeline combined a YOLOv12n detector for muzzle localization with an ImageNet-pretrained EfficientNetB0 classifier for individual identification. Forty-eight cattle (32 adult cows and 16 calves) were photographed on 31 January 2025 (T0) and again on 11 June 2025 (T1), a 131-day interval. Four images per animal were obtained at each session, producing 384 longitudinal images. The detector-development dataset comprised 565 original images from cattle sampled independently at a slaughterhouse and 210 public Zenodo images, with no animal- or image-level overlap with the longitudinal dataset. The 775 detector images were randomly partitioned at image level into training (
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