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Object detection in remote sensing images based on one-class classification

机译:基于一类分类的遥感图像目标检测

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摘要

For remote sensing image understanding, target detection is one of the most important tasks. In this paper, we propose one object detection method based on region proposal detection via active contour model and detection based on one-class classification method. The large scale remote sensing image is split into several connected components. And then, the proposed algorithm detects the object from the background. The proposed algorithm has been tested on several scenes of real unmanned aerial vehicle image datasets, and achieves promising results.
机译:对于遥感图像的理解,目标检测是最重要的任务之一。在本文中,我们提出了一种基于主动轮廓模型的区域提议检测和基于一类分类方法的检测的物体检测方法。大规模遥感影像被分成几个相连的部分。然后,该算法从背景中检测出物体。所提出的算法已经在真实的无人机图像数据集的多个场景上进行了测试,并取得了可喜的成果。

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