ROAD SURFACE DETECTION FROM MOBILE LIDAR DATA

13 citations as recorded by crossref.

1. Real-Time Road Surface LiDAR SLAM Based on Dead-Reckoning Assisted Registration J. Jo et al. https://doi.org/10.1109/TIV.2024.3425929
2. Road potholes detection from MLS point clouds X. Ma et al. https://doi.org/10.1088/1361-6501/acdb8d
3. Autonomous Wind-Turbine Blade Inspection Using LiDAR-Equipped Unmanned Aerial Vehicle M. Car et al. https://doi.org/10.1109/ACCESS.2020.3009738
4. Investigation of landslide-based road surface deformation in mountainous areas with single period UAV data M. Zeybek & S. Biçici https://doi.org/10.1080/10106049.2022.2142969
5. Performance of mobile terrestrial LiDAR systems for data collection at high speeds on highways N. Vu et al. https://doi.org/10.1007/s41324-026-00711-x
6. Road surface and inventory extraction from mobile LiDAR point cloud using iterative piecewise linear model M. Zeybek & S. Biçici https://doi.org/10.1088/1361-6501/acb78d
7. 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
8. Effectiveness of Training Sample and Features for Random Forest on Road Extraction from Unmanned Aerial Vehicle-Based Point Cloud S. Biçici & M. Zeybek https://doi.org/10.1177/03611981211029645
9. Automated Modeling of Road Networks for High-Definition Maps in OpenDRIVE Format Using Mobile Mapping Measurements K. Chiang et al. https://doi.org/10.3390/geomatics2020013
10. Enhance Road Detection Data Processing of LiDAR Point Clouds to Specifically Identify Unmarked Gravel Rural Roads R. Huston & J. Wilhelm https://doi.org/10.1115/1.4066189
11. Road surface segmentation from MLS point clouds based on TDANet X. Ma et al. https://doi.org/10.1088/2631-8695/ae22c3
12. Extraction of Road Lane Markings from Mobile LiDAR Data M. Zeybek https://doi.org/10.1177/0361198120981948
13. Advantages of MTL solutions in Vietnam's transportation infrastructure surveying: a case study of the AU20 system N. Vu & N. Luong https://doi.org/10.1080/00396265.2025.2452796