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The aim is to enhance detection of cotton leaf diseases in complex backgrounds and for small-target diseases using a modified YOLO model.

July 26, 2026Scientific ReportsOpen Access

MSE-YOLOv8n: a cotton leaf disease detection model for complex backgrounds and small targets

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Randomized trial shows improved disease detection in cotton leaves, suggesting better agricultural outcomes.

The aim is to enhance detection of cotton leaf diseases in complex backgrounds and for small-target diseases using a modified YOLO model.
Developed a composite algorithm M-S-E-YOLOv8n optimized from YOLOv8n.
Integrated an MSAA module for better background processing.
Incorporated a Smallhead detection head for improved recognition of small targets.
M-S-E-YOLOv8n achieved a mAP@0.50:0.95 increase of 1.4%.
Precision improved by 3.7% and recall by 2.9% compared to original YOLOv8n.

Xue et al. (2026) studied this question.

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