Explainable YOLO architectures for egg size measurement and classification

Abstract The poultry industry faces growing demands for automated, high-precision egg grading systems to ensure quality control and meet market standards. Traditional methods relying on manual inspection are time-consuming, subjective, and prone to human error. Although state-of-the-art YOLO archite...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Elsayed M. Atwa, Ibrahim Gad, Qiong Liu, Yunxiao Jiang, M. M. Abd El-Raouf, Shupeng He, Hongjian Lin, Jinming Pan
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Nature Portfolio 2026-04-01
Sarja:	Scientific Reports
Aiheet:	YOLO Egg size Poultry industry Egg quality XAI
Linkit:	https://doi.org/10.1038/s41598-026-49155-1
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