YOLOv8-Ghost-QWA: A Lightweight Model with Quadro-Weighted Attention for Tomato Maturity Segmentation
Robust, real-time recognition of tomato maturity in unconstrained field conditions remains a critical bottleneck for autonomous harvesting platforms, as manual methods are costly and labor-intensive. Existing approaches, such as Vision Transformer-based models and YOLO variants with attention module...
-д хадгалсан:
| Үндсэн зохиолчид: | , , , |
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| Формат: | Artigo |
| Хэл сонгох: | Inglês |
| Хэвлэсэн: |
Taylor & Francis Group
2026-12-01
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| Цуврал: | Applied Artificial Intelligence |
| Онлайн хандалт: | https://www.tandfonline.com/doi/10.1080/08839514.2026.2684110 |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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