SUBMANIFOLD SPARSE CONVOLUTIONAL NETWORKS FOR SEMANTIC SEGMENTATION OF LARGE-SCALE ALS POINT CLOUDS

27 citations as recorded by crossref.

1. ACE-of-SPADEs: Accelerating Spatially Sparse Convolution for 3D Scene Understanding O. Omer et al.
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4. Towards intelligent ground filtering of large-scale topographic point clouds: A comprehensive survey N. Qin et al.
5. Multiple Random Observation Strategy for Enhanced ALS Point Cloud Segmentation H. Dai et al.
6. Classification of ALS Point Clouds Using End-to-End Deep Learning L. Winiwarter et al.
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8. Incorporating Handcrafted Features into Deep Learning for Point Cloud Classification P. Hsu & Z. Zhuang
9. Human‐in‐the‐loop development of spatially adaptive ground point filtering pipelines—An archaeological case study M. Doneus et al.
10. 3DMASC: Accessible, explainable 3D point clouds classification. Application to bi-spectral topo-bathymetric lidar data M. Letard et al.
11. Building a Fully-Automatized Active Learning Framework for the Semantic Segmentation of Geospatial 3D Point Clouds M. Kölle et al.
12. A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments S. Jin et al.
13. Airborne Laser Scanning Point Cloud Classification Using the DGCNN Deep Learning Method E. Widyaningrum et al.
14. DAPNet++: density adaptive PointNet + + for airborne laser scanning data Z. Akbulut & F. Karsli
15. HAVANA: Hard Negative Sample-Aware Self-Supervised Contrastive Learning for Airborne Laser Scanning Point Cloud Semantic Segmentation Y. Zhang et al.
16. Classification of airborne 3D point clouds regarding separation of vegetation in complex environments D. Bulatov et al.
17. BathyNet: A Deep Neural Network for Water Depth Mapping from Multispectral Aerial Images G. Mandlburger et al.
18. Terrain-Net: A Highly-Efficient, Parameter-Free, and Easy-to-Use Deep Neural Network for Ground Filtering of UAV LiDAR Data in Forested Environments B. Li et al.
19. Transfer Learning in Earth Observation Data Analysis: A review A. Nowakowski et al.
20. A novel projection map driven multimodal fusion framework for ALS point cloud semantic segmentation P. Li et al.
21. A Comparison of Deep Learning Methods for Airborne Lidar Point Clouds Classification N. Li et al.
22. Juggling with representations: On the information transfer between imagery, point clouds, and meshes for multi-modal semantics D. Laupheimer & N. Haala
23. Individual Tree Detection in Urban ALS Point Clouds with 3D Convolutional Networks S. Schmohl et al.
24. Archaeological Ground Point Filtering of Airborne Laser Scan Derived Point-Clouds in a Difficult Mediterranean Environment M. Doneus et al.
25. CBF-Net: An Adaptive Context Balancing and Feature Filtering Network for Point Cloud Classification Q. Zang et al.
26. A Dual Attention Neural Network for Airborne LiDAR Point Cloud Semantic Segmentation K. Zhang et al.
27. A Hybrid Framework Combining Data-Driven and Catenary-Based Methods for Wide-Area Powerline Sag Estimation Y. Wu et al.