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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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/14/8085 |
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