Synergy of sampling techniques and ensemble classifiers for classification of urban environments using full-waveform LiDAR data

Author:

Azadbakht Mohsen,Fraser Clive S.,Khoshelham Kourosh

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference54 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. adabag: an R package for classification with boosting and bagging;Alfaro;J. Stat. Softw.,2013

3. Improved urban scene classification using full-waveform LiDAR;Azadbakht;Photogramm. Eng. Remote Sens.,2016

4. A sparsity-based regularization approach for deconvolution of full-waveform airborne LiDAR data;Azadbakht;Remote Sens.,2016

5. Separability of targets in urban areas using features from full-waveform LiDARA data;Azadbakht,2015

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