Stressor-Specific Anomaly Detection System in Group-Housed Growing Pigs Through Combined Computer Vision-Machine Learning Framework: A Pilot Study

This study proposed a multi-class anomaly detection framework for group-housed pigs by integrating computer vision and machine learning. Nine classification algorithms were trained to identify five pig conditions—normal, heat stress, poor ventilation, infection, and recovery—using 10 combinations of...

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Detalhes bibliográficos

Principais autores:	Eddiemar B. Lagua, Hong-Seok Mun, Md Sharifuzzaman, Md Kamrul Hasan, Ahsan Mehtab, Jin-Gu Kang, Hae-Rang Park, Young-Hwa Kim, Chul-Ju Yang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-05-01
Colecção:	AI
Assuntos:	smart farm health monitoring object detection automatic system artificial intelligence
Acesso em linha:	https://www.mdpi.com/2673-2688/7/6/184
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