A Multi-Granularity Gated Image-Level Supervised Network (MGG-ISCNet) for Spike Counting in <i>Agropyron cristatum</i> (L.) Gaertn

Accurate counting of spikes in crested wheatgrass, an important forage resource, is essential for breeding and yield evaluation. However, traditional manual counting is inefficient, and instance-level supervised methods face challenges such as high annotation costs and counting errors caused by over...

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Autors principals:	Lihua Guan, Ziyu Ding, Meng’an Song, Xinyuan He, Qiqi Wang, Ruopu Zan, Zhangru Gao, Xiang Li, Yan Zhao, Dongyan Zhang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-12-01
Col·lecció:	Agronomy
Matèries:	crested wheatgrass spike counting detection image-level supervision lightweight model field phenotyping
Accés en línia:	https://www.mdpi.com/2073-4395/15/12/2805
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