ROBUST AND EFFECTIVE AIRBORNE LIDAR POINT CLOUD CLASSIFICATION BASED ON HYBRID FEATURES
L. F. Liao,S. J. Tang,J. H. Liao,W. X. Wang,X. M. Li,and R. Z. Guo
L. F. Liao
Research Institute for Smart Cities, School of Architecture and Urban Planning & Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen University, Shenzhen, P.R. China
S. J. Tang
Research Institute for Smart Cities, School of Architecture and Urban Planning & Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen University, Shenzhen, P.R. China
J. H. Liao
Research Institute for Smart Cities, School of Architecture and Urban Planning & Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen University, Shenzhen, P.R. China
W. X. Wang
Research Institute for Smart Cities, School of Architecture and Urban Planning & Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen University, Shenzhen, P.R. China
X. M. Li
Research Institute for Smart Cities, School of Architecture and Urban Planning & Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen University, Shenzhen, P.R. China
R. Z. Guo
Research Institute for Smart Cities, School of Architecture and Urban Planning & Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen University, Shenzhen, P.R. China
Viewed
Total article views: 416 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
265
135
16
416
10
12
HTML: 265
PDF: 135
XML: 16
Total: 416
BibTeX: 10
EndNote: 12
Views and downloads (calculated since 30 May 2022)
Cumulative views and downloads
(calculated since 30 May 2022)
Viewed (geographical distribution)
Total article views: 402 (including HTML, PDF, and XML)
Thereof 402 with geography defined
and 0 with unknown origin.