A random forest classifier based on pixel comparison features for urban LiDAR data-Reference-Cited by-同舟云学术

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A random forest classifier based on pixel comparison features for urban LiDAR data

Published:2019-02 Issue: Volume:148 Page:75-86
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Wang Chisheng^ORCID,Shu Qiqi,Wang Xinyu,Guo Bo,Liu Peng,Li Qingquan

Funder

National Natural Science Foundation of China

Natural Science Funding of Shenzhen University

Shenzhen Scientific Research and Development Funding Program

Open Fund of the State Key Laboratory of Earthquake Dynamics

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference41 articles.

1. Backscatter coefficient as an attribute for the classification of full-waveform airborne laser scanning data in urban areas;Alexander;ISPRS J. Photogramm. Remote Sens.,2010

2. Bartels, M., Wei, H., 2006. Rule-based improvement of maximum likelihood classified LIDAR data fused with co-registered bands. In: Paper presented at Proceedings of Annual Conference of the Remote Sensing and Photogrammetry Society.

3. Random forests;Breiman;Mach. Learn.,2001

4. LOF: identifying density-based local outliers;Breunig;Int. Conf. Manage. Data,2000

5. Land use classification from lidar data and ortho-images in a rural area;Bujan;Photogramm. Rec.,2012

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