SUPERVOXEL-BASED MULTI-SCALE POINT CLOUD SEGMENTATION USING FNEA FOR OBJECT-ORIENTED ROCK SLOPE CLASSIFICATION USING TLS

9 citations as recorded by crossref.

1. A new method for recognizing discontinuities from 3D point clouds in tunnel construction environments X. Peng et al. 10.1016/j.tust.2024.105955
2. An algorithm for measuring landslide deformation in terrestrial lidar point clouds using trees L. Weidner et al. 10.1007/s10346-021-01723-4
3. Classification of urban functional zones through deep learning S. Izzo et al. 10.1007/s00521-021-06822-w
4. Accuracy of Rockfall Volume Reconstruction from Point Cloud Data—Evaluating the Influences of Data Quality and Filtering G. Walton & L. Weidner 10.3390/rs15010165
5. Targeted Rock Slope Assessment Using Voxels and Object-Oriented Classification I. Farmakis et al. 10.3390/rs13071354
6. Efficient measurement for surface displacement of slope retaining structures with 3D point cloud semantic modeling X. Liu et al. 10.1016/j.measurement.2025.117631
7. Superpixel and Supervoxel Segmentation Assessment of Landslides Using UAV-Derived Models I. Farmakis et al. 10.3390/rs14225668
8. Generalized Extraction of Bolts, Mesh, and Rock in Tunnel Point Clouds: A Critical Comparison of Geometric Feature-Based Methods Using Random Forest and Neural Networks L. Weidner & G. Walton 10.3390/rs16234466
9. A depth information-based method to enhance rainfall-induced landslide deformation area identification C. Yuan et al. 10.1016/j.measurement.2023.113288