Object Detection on Aerial Image by Using High-Resolutuion Network

Zhiyan Bao, Chen Xing, Xi Liang
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Abstract

To detect trespassing in images captured by drones for water conservancy facilities inspection, this paper proposes a method that adapts Hight-Resolution Net to reserve high resolution features for improving detecting results. To detect trespassing target with small scale, this method parallels low-resolution and high-resolution conventical feature maps to reserve high-resolution features, besides that multi-scale fusions are conducted to enhance feature maps with different resolutions. Compare to Faster R-CNN, proposed method achieves 1.7% higher mAP on small targets.
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基于高分辨率网络的航空图像目标检测
为了检测无人机采集的水利设施检测图像中的非法侵入,本文提出了一种利用high - resolution Net保留高分辨率特征以提高检测效果的方法。为了检测小尺度入侵目标,该方法对低分辨率和高分辨率常规特征图进行并行处理,保留高分辨率特征,并进行多尺度融合,增强不同分辨率的特征图。与Faster R-CNN相比,本文方法在小目标上的mAP提高了1.7%。
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