Cotton-YOLO-Seg: An Enhanced YOLOV8 Model for Impurity Rate Detection in Machine-Picked Seed Cotton

The detection of the impurity rate in machine-picked seed cotton is crucial for precision agriculture. This study proposes a novel Cotton-YOLO-Seg cotton-impurity instance segmentation algorithm based on the you only look once version 8 small segmentation model (Yolov8s-Seg). The algorithm achieves...

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Autors principals:	Long Jiang, Weitao Chen, Hongtai Shi, Hongwen Zhang, Lei Wang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-09-01
Col·lecció:	Agriculture
Matèries:	impurity rate of machine-picked seed cotton machine vision impurity instance segmentation Yolov8s-seg improvements
Accés en línia:	https://www.mdpi.com/2077-0472/14/9/1499
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