UNSUPERVISED DOMAIN ADAPTATION USING A TEACHER-STUDENT NETWORK FOR CROSS-CITY CLASSIFICATION OF SENTINEL-2 IMAGES
A machine learning algorithm in remote sensing often fails in the inference of a data set which has a different geographic location than the training data. This is because data of different locations have different underlying distributions caused by complicated reasons, such as the climate and the c...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-08-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/1569/2020/isprs-archives-XLIII-B2-2020-1569-2020.pdf |