FULLY CONVOLUTIONAL NETWORKS FOR GROUND CLASSIFICATION FROM LIDAR POINT CLOUDS

22 citations as recorded by crossref.

1. Virtual Disassembling of Historical Edifices: Experiments and Assessments of an Automatic Approach for Classifying Multi-Scalar Point Clouds into Architectural Elements A. Murtiyoso & P. Grussenmeyer
2. Big Data Geospatial Processing for Massive Aerial LiDAR Datasets D. Deibe et al.
3. Mapping the Topographic Features of Mining-Related Valley Fills Using Mask R-CNN Deep Learning and Digital Elevation Data A. Maxwell et al.
4. Classification of ALS Point Clouds Using End-to-End Deep Learning L. Winiwarter et al.
5. SC-CNN: LiDAR point cloud filtering CNN under slope and copula correlation constraint R. Chen et al.
6. Vertical slice equal sampling and transformer network for point cloud ground filtering W. Wen et al.
7. A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments S. Jin et al.
8. Automatic Workflow for Roof Extraction and Generation of 3D CityGML Models from Low-Cost UAV Image-Derived Point Clouds A. Murtiyoso et al.
9. Correction of Low Vegetation Impact on UAV-Derived Point Cloud Heights With U-Net Networks W. Gruszczynski et al.
10. RETRACTED ARTICLE: Flexible big data approach for geospatial analysis R. Malik & M. Nishi
11. Advanced Fully Convolutional Networks for Agricultural Field Boundary Detection A. Taravat et al.
12. A deep neural network based on U-Net for classifying airborne LiDAR data F. Uray & A. Varlık
13. A Multi-scale Convolutional Neural Network for Precise Digital Terrain Model Extraction from Digital Surface Models A. Al-Fugara et al.
14. Searching for Viking Age Fortresses with Automatic Landscape Classification and Feature Detection D. Stott et al.
15. Full-Waveform Airborne LiDAR Data Classification Using Convolutional Neural Networks S. Zorzi et al.
16. Ground and Multi-Class Classification of Airborne Laser Scanner Point Clouds Using Fully Convolutional Networks A. Rizaldy et al.
17. A new weakly supervised approach for ALS point cloud semantic segmentation P. Wang & W. Yao
18. Feature selection for airborne LiDAR data filtering: a mutual information method with Parzon window optimization Z. Cai et al.
19. A deep learning approach to identify smoke plumes in satellite imagery in near-real time for health risk communication A. Larsen et al.
20. A Dual Attention Neural Network for Airborne LiDAR Point Cloud Semantic Segmentation K. Zhang et al.
21. A New Approach for Ground Filtering of Airborne Laser Scanning Data Using PointNet++ Z. Akbulut et al.
22. Enhancing the Accuracy of Digital Terrain Model in Complex Coastal Landscape: Case Study at Jupiter Inlet Lighthouse ONA, Florida N. Manikkavasagam et al.