ROAD TYPE CLASSIFICATION OF MLS POINT CLOUDS USING DEEP LEARNING

6 citations as recorded by crossref.

1. Different KNN parameters on road surface extraction from UAV-based point cloud under several machine learning algorithms S. Biçici https://doi.org/10.1088/1361-6501/ad5ab9
2. An Automatic Road Surface Segmentation in Non-Urban Environments: A 3D Point Cloud Approach With Grid Structure and Shallow Neural Networks M. Dowajy et al. https://doi.org/10.1109/ACCESS.2024.3372431
3. Combining 3D Urban Objects from All Around the World to Improve Object Classification and Semantic Segmentation O. Bayrak et al. https://doi.org/10.1007/s41064-025-00374-7
4. Engineering-aware semantic mapping of constrained urban streets for 3D swept path analysis in modular integrated construction logistics F. Wang et al. https://doi.org/10.1016/j.autcon.2026.107306
5. A Handheld LiDAR-Based Semantic Automatic Segmentation Method for Complex Railroad Line Model Reconstruction J. Chen et al. https://doi.org/10.3390/rs15184504
6. Road surface segmentation from MLS point clouds based on TDANet X. Ma et al. https://doi.org/10.1088/2631-8695/ae22c3