EDSC-HRAFNet: An apple tree branch semantic segmentation model for harvesting robots under complex orchard conditions
Accurate semantic understanding of tree branches is critical for orchard harvesting robots in automated fruit harvesting and pruning. Existing methods suffer from low detection accuracy and limited adaptability in complex orchard environments. This paper proposes a novel apple tree branch semantic s...
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| Автори: | , , , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
KeAi Communications Co., Ltd.
2026-06-01
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| Серія: | Artificial Intelligence in Agriculture |
| Предмети: | |
| Онлайн доступ: | http://www.sciencedirect.com/science/article/pii/S2589721726000061 |
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