无人机
计算机科学
人工智能
计算机视觉
目标检测
比例(比率)
模式识别(心理学)
地理
遗传学
地图学
生物
作者
Jun-Hwa Kim,Nam‐Ho Kim,Chee Sun Won
标识
DOI:10.1109/icassp49357.2023.10095516
摘要
Detecting drones in a video is a challenging problem due to their dynamic movements and varying range of scales. Moreover, since drone detection is often required for security, it should be as fast as possible. In this paper, we modify the state-of-the-art YOLO-V8 to achieve fast and reliable drone detection. Specifically, we add Multi-Scale Image Fusion and P2 Layer to the medium-size model (M-model) of YOLO-V8. Our model was evaluated in the 6th WOSDETC challenge.
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