High-Quality Road Detection Using U-Net-Based Semantic Segmentation with High-Resolution Orthophotos and DSM Data in Urban Environments

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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Bibliographic Details
Main Authors:	M. Fawzy, A. Juhász, A. Barsi
Format:	Article
Language:	English
Published:	Copernicus Publications 2025-07-01
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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