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首页> 外文会议>International Geoscience and Remote Sensing Symposium >Weak Target Detection in High-Resolution Remote Sensing Images by Combining Super-Resolution and Deformable FPN
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Weak Target Detection in High-Resolution Remote Sensing Images by Combining Super-Resolution and Deformable FPN

机译：通过组合超分辨率和可变形FPN的高分辨率遥感图像中的目标检测弱

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摘要

Weak target detection plays an important role in military and civilian fields. However, due to the limitation of the target size and the influence of complex background, the detection of weak target is a huge challenge. Therefore, based on high-resolution remote sensing image, this paper proposes a weak target detection network which combines super-resolution and deformable convolution. Firstly, the high-resolution remote sensing image is expanded and enhanced to eliminate the influence of complex background. Secondly, a detection network based on the deformable convolution and feature pyramid network (FPN) is used to solve the problem of less information caused by the fewer target pixels. In addition, this paper establishes a detection dataset only containing weak vehicles. The experimental results show that the proposed method achieves better detection results in the weak target detection problem.
机译：弱势目标检测在军事和文职领域发挥着重要作用。然而，由于目标尺寸的限制和复杂背景的影响，弱目标的检测是一个巨大的挑战。因此，基于高分辨率遥感图像，本文提出了一种薄弱的目标检测网络，其结合了超级分辨率和可变形卷积。首先，扩展和增强高分辨率遥感图像以消除复杂背景的影响。其次，基于可变形卷积和特征金字塔网络（FPN）的检测网络用于解决由目标像素越少的信息的问题。此外，本文仅建立了仅包含弱电车的检测数据集。实验结果表明，该方法达到了弱目标检测问题的检测结果。

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