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Low-altitude UAV Detection Method Based on One-staged Detection Framework

机译:基于一阶段检测框架的低空无人机检测方法

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Illegal flight of unmanned aerial vehicles (UAVs) poses serious threats to the public and national security. With the characteristics of small size and low flight height, UAVs are difficult for the traditional air-defense system to detect. Therefore, to deal with the illegal UAV flight, this paper proposed a state-of-the art low-altitude UAV detection method. Firstly, a large-scale UAV data set including multiple kinds of UAVs is collected and constructed. Then, based on one stage detection framework, the UAV detection (UAVDet) network is presented with the improvement of more detection scales, utilization of focal loss and specific data augmentation. Experiment results show that the proposed UAV detection method has significant improvement on UAV detection performance, and it is competent to achieve real-time and effective UAV detection.
机译:无人机的非法飞行对公共和国家安全构成严重威胁。由于具有体积小,飞行高度低的特点,传统的防空系统很难检测到无人机。因此,为了应对非法无人机飞行,本文提出了一种最新的低空无人机检测方法。首先,收集并构建了包含多种无人机的大规模无人机数据集。然后,在一个阶段的检测框架的基础上,提出了无人机检测网络(UAVDet),该网络具有更大的检测范围,聚焦损失的利用和特定数据的增强。实验结果表明,所提出的无人机检测方法对无人机的检测性能有较大的提高,能够实时有效地进行无人机检测。

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