U-net Network for Building Information Extraction of Remote-Sensing Imagery

Jingtan Li, Maolin Xu, Hongling Xiu


With the resolution of remote sensing images is getting higher and higher, high-resolution remote sensing images are widely used in many areas. Among them, image information extraction is one of the basic applications of remote sensing images. In the face of massive high-resolution remote sensing image data, the traditional method of target recognition is difficult to cope with. Therefore, this paper proposes a remote sensing image extraction based on U-net network. Firstly, the U-net semantic segmentation network is used to train the training set, and the validation set is used to verify the training set at the same time, and finally the test set is used for testing. The experimental results show that U-net can be applied to the extraction of buildings.


High resolution remote sensing image, FCN; U-net, Building extraction

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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