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Stacked U-Nets for Ground Material Segmentation in Remote Sensing Imagery
AbstractWe present a semantic segmentation algorithm for RGB remote sensing images. Our method is based on the Dilated Stacked U-Nets architecture. This state-of-the-art method has been shown to have good performance in other applications. We perform additional post-processing by blending image tiles and degridding the result. Our method gives competitive results on the DeepGlobe dataset.
Related Material
[pdf][bibtex]@InProceedings{Ghosh_2018_CVPR_Workshops,
author = {Ghosh, Arthita and Ehrlich, Max and Shah, Sohil and Davis, Larry S. and Chellappa, Rama},
title = {Stacked U-Nets for Ground Material Segmentation in Remote Sensing Imagery},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2018}
}
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