High-Quality Road Detection Using U-Net-Based Semantic Segmentation with High-Resolution Orthophotos and DSM Data in Urban Environments
Road detection and recognition from high-resolution geospatial data in urban environments is critical for numerous applications, including urban planning, navigation systems, and automated driving technologies. This study explores the potential of deep learning methodologies, specifically U-Net-base...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
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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-G-2025/459/2025/isprs-archives-XLVIII-G-2025-459-2025.pdf |
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