COMPARISON OF DEEP LEARNING ARCHITECTURES FOR THE SEMANTIC SEGMENTATION OF SLUM AREAS FROM SATELLITE IMAGES
The mapping of slum areas is an important task when considering the necessity for an inclusive, safe and resilient cities. While many methods exist in this regard, the use of machine learning and more specifically deep learning has gained traction in recent years. In this paper, we present a systema...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-12-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1439/2023/isprs-archives-XLVIII-1-W2-2023-1439-2023.pdf |