Tree Trunk and Obstacle Detection in Apple Orchard Based on Improved YOLOv5s Model

In this paper, we propose a tree trunk and obstacle detection method in a semistructured apple orchard environment based on improved YOLOv5s, with an aim to improve the real-time detection performance. The improvement includes using the K-means clustering algorithm to calculate anchor frame and addi...

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Detalles Bibliográficos

Principais autores:	Fei Su, Yanping Zhao, Yanxia Shi, Dong Zhao, Guanghui Wang, Yinfa Yan, Linlu Zu, Siyuan Chang
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2022-10-01
Series:	Agronomy
Assuntos:	semistructured orchard environment tree trunk and obstacle detection improved YOLOv5s carrier platform
Acceso en liña:	https://www.mdpi.com/2073-4395/12/10/2427
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