Using multi-scale and hierarchical deep convolutional features for 3D semantic classification of TLS point clouds

Classifying airborne LiDAR point clouds via deep features learned by a multi-scale convolutional neural network

(2018) Ruibin Zhao et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

Automating Parameter Learning for Classifying Terrestrial LiDAR Point Cloud Using 2D Land Cover Maps

(2018) Chen-Chieh Feng et al.   Remote Sensing

A Bayesian-Network-Based Classification Method Integrating Airborne LiDAR Data With Optical Images

(2017) Zhizhong Kang et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Learning multiscale and deep representations for classifying remotely sensed imagery

(2016) Wenzhi Zhao et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

A Multiscale and Hierarchical Feature Extraction Method for Terrestrial Laser Scanning Point Cloud Classification

(2015) Zhen Wang et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers

(2015) Martin Weinmann et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning

(2014) Andrés Serna et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

SVM-Based Classification of Segmented Airborne LiDAR Point Clouds in Urban Areas

(2013) Jixian Zhang et al.   Remote Sensing