A Real-Time Cotton Boll Disease Detection Model Based on Enhanced YOLOv11n

A Real-Time Cotton Boll Disease Detection Model Based on Enhanced YOLOv11n

Existing methods for detecting cotton boll diseases frequently exhibit high rates of <b>both</b> false negatives and false positives under complex field conditions (e.g., lighting variations, shadows, and occlusions) and struggle to achieve real-time performance on edge devices. To addre...

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Bibliographic Details
Main Authors: Lei Yang, Wenhao Cui, Jingqian Li, Guotao Han, Qi Zhou, Yubin Lan, Jing Zhao, Yongliang Qiao
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
detection of cotton boll diseases
YOLOv11
EMA mechanism
partial convolution
loss function
Online Access:https://www.mdpi.com/2076-3417/15/14/8085
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