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Classification of LiDAR Point Clouds Using Supervoxel-Based Detrended Feature and Perception-Weighted Graphical Model

  • Published:2020 Issue: Volume:13 Page:72-88
  • ISSN:1939-1404
  • Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • language:
  • Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Xu YushengORCID,Ye ZhenORCID,Yao WeiORCID,Huang RongORCID,Tong XiaohuaORCID,Hoegner Ludwig,Stilla UweORCID

Funder

National Key Research and Development Program of China Stem Cell and Translational Research

National Natural Science Foundation of China

Bavarian Excellence program based on the Bavarian Elite Aid Act

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Cited by 26 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A comprehensive analysis for classification and regression of surface points based on geodesics and machine learning algorithms;Engineering Computations;2023-10-06

2. Point cloud voxel classification of aerial urban LiDAR using voxel attributes and random forest approach;International Journal of Applied Earth Observation and Geoinformation;2023-04

3. Semantic supported urban change detection using ALS point clouds;International Journal of Applied Earth Observation and Geoinformation;2023-04

4. Joint learning of frequency and spatial domains for dense image prediction;ISPRS Journal of Photogrammetry and Remote Sensing;2023-01

5. Identifying surface points based on machine learning algorithms: a comprehensive analysis;Data Technologies and Applications;2022-11-29
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