SEMANTIC LABELING OF ALS POINT CLOUDS FOR TREE SPECIES MAPPING USING THE DEEP NEURAL NETWORK POINTNET++

8 citations as recorded by crossref.

1. FWNet: Semantic Segmentation for Full-Waveform LiDAR Data Using Deep Learning T. Shinohara et al. 10.3390/s20123568
2. A Convex Hull-Based Feature Descriptor for Learning Tree Species Classification From ALS Point Clouds Y. Lv et al. 10.1109/LGRS.2021.3055773
3. Tree Species Classification of Backpack Laser Scanning Data Using the PointNet++ Point Cloud Deep Learning Method B. Liu et al. 10.3390/rs14153809
4. Tree Species Classification Using Ground-Based LiDAR Data by Various Point Cloud Deep Learning Methods B. Liu et al. 10.3390/rs14225733
5. Segmentation of unbalanced and in-homogeneous point clouds and its application to 3D scanned trees J. Morel et al. 10.1007/s00371-020-01966-7
6. Traffic sign extraction using deep hierarchical feature learning and mobile light detection and ranging (LiDAR) data on rural highways M. Gouda et al. 10.1080/15472450.2022.2074792
7. Semantic Segmentation and Building Extraction from Airborne LiDAR Data with Multiple Return Using PointNet++ Y. Shin et al. 10.3390/app12041975
8. Classification of Typical Tree Species in Laser Point Cloud Based on Deep Learning J. Chen et al. 10.3390/rs13234750