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World Journal of Engineering Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

An Official Publication of Society for Advance Healthcare Research (Reg. No. : 01/01/01/31674/16)

ISSN 2454-695X

Impact Factor : 8.067

ICV : 79.45

WJERT Citation

  All Since 2020
 Citation  172  110
 h-index  7  5
 i10-index  1  0

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Abstract

APPLICATION OF MACHINE LEARNING ALGORITHMS IN LIDAR POINT CLOUD CLASSIFICATION

Trung Nguyen Tu*, Tran Thi Thu Ngan

ABSTRACT

The extraction and classification of features from three-dimensional(3D) LiDAR point clouds have become essential in photogrammetry,remote sensing, and smart city modeling. This study investigates theapplication of a number of supervised machine learning methods forclassifying LiDAR point clouds, including Random Forest, DecisionTree, Naïve Bayes, Neural Networks, AdaBoost, Support VectorMachines (SVM), and K-Nearest Neighbours (K-NN). Experimentswere conducted on two datasets with various geometric and radiometricfeatures. Evaluation measures such F1-Score, Precision, and Recall,and computational time were analyzed. The results demonstrate theeffectiveness of integrating geometric features and ensemble learningstrategies in improving classification performance.

[Full Text Article] [Download Certificate] https://doi.org/10.5281/zenodo.19886044