POINTNET FOR THE AUTOMATIC CLASSIFICATION OF AERIAL POINT CLOUDS

9 citations as recorded by crossref.

1. Deep Ordinal Classification in Forest Areas Using Light Detection and Ranging Point Clouds A. Morales-Martín et al. 10.3390/s24072168
2. Automated bridge component recognition from point clouds using deep learning H. Kim et al. 10.1002/stc.2591
3. 3D point‐cloud spatial expansion by total least‐squares line fitting P. Dąbrowski & M. Zienkiewicz 10.1111/phor.12345
4. An Analysis of Ground-Point Classifiers for Terrestrial LiDAR K. Roberts et al. 10.3390/rs11161915
5. Evaluation of Class Distribution and Class Combinations on Semantic Segmentation of 3D Point Clouds With PointNet E. Barnefske & H. Sternberg 10.1109/ACCESS.2022.3233411
6. LiDAR Point Cloud Recognition of Overhead Catenary System with Deep Learning S. Lin et al. 10.3390/s20082212
7. Airborne Laser Scanning Point Cloud Classification Using the DGCNN Deep Learning Method E. Widyaningrum et al. 10.3390/rs13050859
8. A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models R. Battulwar et al. 10.1016/j.jrmge.2021.01.008
9. Object-level classification of vegetable crops in 3D LiDAR point cloud using deep learning convolutional neural networks R. Jayakumari et al. 10.1007/s11119-021-09803-0