DGBL-YOLOv8s: An Enhanced Object Detection Model for Unmanned Aerial Vehicle Imagery
Unmanned aerial vehicle (UAV) imagery often suffers from significant object scale variations, high target density, and varying distances due to shooting conditions and environmental factors, leading to reduced robustness and low detection accuracy in conventional models. To address these issues, thi...
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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2025-03-01
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| Серии: | Applied Sciences |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2076-3417/15/5/2789 |
| Метки: |
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