YOLOv8n-DSDL: A lightweight dual-backbone network with decoupled self-attention for cotton maturity detection
Abstract Accurate monitoring of cotton maturity is crucial for improving both yield and quality in cotton production. However, existing models often suffer from low detection accuracy and poor adaptability due to challenges such as varietal diversity, rapid changes in maturity stages, difficulty in...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44443-025-00081-8 |
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