DDM-YOLO: A lightweight oriented detection model for mature daylily fruits in complex environments
Abstract Accurate and robust recognition of daylily flower buds at the pre-bloom stage is essential for timely harvesting and quality preservation, yet remains highly challenging under natural field conditions due to the buds’ slender morphology, diverse orientations, dense distribution, and frequen...
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| Hauptverfasser: | , , , , , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Springer
2026-02-01
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| Schriftenreihe: | Journal of King Saud University: Computer and Information Sciences |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1007/s44443-026-00559-z |
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