Improved YOLOv11 for Lightweight and Accurate Detection of Flax Diseases and Pests in Complex Field Environments

Timely and accurate detection of flax (<i>Linum usitatissimum</i> L.) pests and diseases is essential for ensuring stable yield and product quality. Nevertheless, practical field deployment remains challenging due to complex backgrounds, large variations in target scale, and limited computational re...

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Bibliografische Detailangaben

Hauptverfasser:	Pengyan Wang, Chengshuai Li, Linjing Wei, Yue Li, Linhai Guo
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2026-03-01
Schriftenreihe:	Agriculture
Schlagworte:	flax pest and disease detection lightweight object detection YOLOv11 instance-level data augmentation deep learning
Online-Zugang:	https://www.mdpi.com/2077-0472/16/7/741
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