DEEP FEW-SHOT LEARNING FOR BI-TEMPORAL BUILDING CHANGE DETECTION
In real-world applications (e.g., change detection), annotating images is very expensive. To build effective deep learning models in these applications, deep few-shot learning methods have been developed and prove to be a robust approach in small training data. The study of building change detection...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2021-08-01
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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/XLIV-M-3-2021/99/2021/isprs-archives-XLIV-M-3-2021-99-2021.pdf |