基于Yolo-V8的高速无人机检测

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI:10.1109/ICASSP49357.2023.10095516

Jun-Hwa Kim, Namho Kim, C. Won

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引用次数: 7

摘要

由于无人机的动态运动和尺度范围的变化，在视频中检测无人机是一个具有挑战性的问题。此外，由于无人机检测经常需要安全，因此应该尽可能快。在本文中，我们修改了最先进的YOLO-V8，以实现快速可靠的无人机检测。具体而言，我们将多尺度图像融合和P2层添加到YOLO-V8的中型模型(M-model)中。我们的模型在第六届WOSDETC挑战赛中进行了评估。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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High-Speed Drone Detection Based On Yolo-V8

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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ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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