A feature perturbation weakly supervised learning network for airborne multispectral LiDAR pointcloud classification
Currently, most pointcloud classification methods heavily rely on huge numbers of labeled samples. Notably, labeling a large-scale multispectral LiDAR (MS-LiDAR) pointcloud is time-consuming and costly. To address this issue, we propose a feature perturbation weakly supervised network for classifyin...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-03-01
|
| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224000372 |