GEOMETRIC FEATURES AND THEIR RELEVANCE FOR 3D POINT CLOUD CLASSIFICATION

42 citations as recorded by crossref.

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20. A hierarchical deep neural network with iterative features for semantic labeling of airborne LiDAR point clouds Y. Yang et al. https://doi.org/10.1016/j.cageo.2021.104932
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22. Toward a Data Fusion Index for the Assessment and Enhancement of 3D Multimodal Reconstruction of Built Cultural Heritage A. Pamart et al. https://doi.org/10.3390/rs15092408
23. Application-Oriented Evaluation of Superpoint Transformer for Bridge Component Segmentation in Terrestrial LiDAR Point Clouds K. Itakura et al. https://doi.org/10.1109/ACCESS.2026.3736669
24. Improvement of 3D LiDAR point cloud classification of urban road environment based on random forest classifier M. Mohamed et al. https://doi.org/10.1080/10106049.2022.2102218
25. Metrological Analysis with Covariance Features of Micro-Channels Fabricated with a Femtosecond Laser M. Verdi et al. https://doi.org/10.3390/metrology4030024
26. Machine Learning Generalisation across Different 3D Architectural Heritage E. Grilli & F. Remondino https://doi.org/10.3390/ijgi9060379
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35. Robust Building Detection in Urban Environments from Airborne LiDAR Data: A Geometry-Based Approach R. dos Santos & M. Galo https://doi.org/10.1109/JSTARS.2024.3391050
36. Inferring an animal’s environment through biologging: quantifying the environmental influence on animal movement J. Eikelboom et al. https://doi.org/10.1186/s40462-020-00228-4
37. Automatic tree detection in varying urban environments using airborne LiDAR data R. dos Santos et al. https://doi.org/10.1007/s12518-026-00720-3
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39. Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey M. Weinmann et al. https://doi.org/10.1007/s41064-021-00163-y
40. A Knowledge-Based Multi-Scale Adaptive Classification Approach for Mobile Laser Scanning Point Clouds in Urban Scenes M. Zheng et al. https://doi.org/10.1109/ACCESS.2023.3335607
41. Evaluation of Class Distribution and Class Combinations on Semantic Segmentation of 3D Point Clouds With PointNet E. Barnefske & H. Sternberg https://doi.org/10.1109/ACCESS.2022.3233411
42. Methodology for Identifying Optimal Pedestrian Paths in an Urban Environment: A Case Study of a School Environment in A Coruña, Spain D. Fernández-Arango et al. https://doi.org/10.3390/smartcities7030060