Deep learning assisted exponential waveform decomposition for bathymetric LiDAR

6 citations as recorded by crossref.

1. CRMF-Net: A Multimodal Fusion Network for Water–Land Classification From Single-Wavelength Bathymetric LiDAR W. Li et al. https://doi.org/10.1109/JSTARS.2026.3655350
2. Progress on methods for waveform processing and target feature inversion based on full-waveform LiDAR J. Fang et al. https://doi.org/10.67704/oep.2026.260001
3. Enhancing macrophyte sub-classification through neighborhood-independent full-waveform LiDAR J. Rhomberg-Kauert et al. https://doi.org/10.1016/j.ophoto.2026.100144
4. A novel strategy of full-waveform light detection and ranging bathymetry based on spatial gram angle difference field conversion and deep-learning network architecture Y. Chen et al. https://doi.org/10.1016/j.rse.2025.114615
5. Physics-informed waveform decomposition with scene adaptation for airborne laser bathymetry B. Hu et al. https://doi.org/10.1364/AO.597685
6. HydroBound-ML: Automated Water-Surface-Mask Generation for Airborne Lidar Bathymetry Processing Using Hybrid Machine Learning and Object-Based Image Analysis P. Wróblewski & A. Fryśkowska-Skibniewska https://doi.org/10.3390/s26196065