EXPLORING CROSS-CITY SEMANTIC SEGMENTATION OF ALS POINT CLOUDS

6 citations as recorded by crossref.

1. Multimodal Co-Learning for Building Change Detection: A Domain Adaptation Framework Using VHR Images and Digital Surface Models Y. Xie et al. https://doi.org/10.1109/TGRS.2024.3362680
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3. 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 https://doi.org/10.3390/rs16234466
4. Transfer Learning Based on Multi-Branch Architecture Feature Extractor for Airborne LiDAR Point Cloud Semantic Segmentation with Few Samples J. Yuan et al. https://doi.org/10.3390/rs17152618
5. Standard Classes for Urban Topographic Mapping with ALS: Classification Scheme and a First Implementation A. Walicka & N. Pfeifer https://doi.org/10.3390/rs17152731
6. Multiprototype Relational Network for Few-Shot ALS Point Cloud Semantic Segmentation by Transferring Knowledge From Photogrammetric Point Clouds M. Dai et al. https://doi.org/10.1109/TGRS.2024.3364181