AI Era Survival: Using YOLOv3 for Accurate Pig Detection
The article explains how YOLOv3’s architectural upgrades—Darknet‑53 backbone, three‑scale feature fusion, refined anchors and multi‑label classification, plus dynamic input sizing—enable a pig‑recognition model trained on 2,456 images to achieve up to 20% higher detection rates and AP scores of 0.673–0.981.
