COMPARISON OF TRADITIONAL AND MACHINE LEARNING BASE METHODS FOR GROUND POINT CLOUD LABELING

6 citations as recorded by crossref.

1. Review of Automatic Processing of Topography and Surface Feature Identification LiDAR Data Using Machine Learning Techniques Z. Gharineiat et al. 10.3390/rs14194685
2. Deep learning for filtering the ground from ALS point clouds: A dataset, evaluations and issues N. Qin et al. 10.1016/j.isprsjprs.2023.06.005
3. Research on Fine-Scale Terrain Construction in High Vegetation Coverage Areas Based on Implicit Neural Representations Y. Zhang et al. 10.3390/su17031320
4. Automatic Filtering of Lidar Building Point Cloud in Case of Trees Associated to Building Roof F. Tarsha Kurdi et al. 10.3390/rs14020430
5. Performance of unsupervised machine learning methods using chi-squared weights for LiDAR point cloud filtering in urban areas A. Sen et al. 10.1080/14498596.2021.2013329
6. Towards intelligent ground filtering of large-scale topographic point clouds: A comprehensive survey N. Qin et al. 10.1016/j.jag.2023.103566