Classification of lidar point clouds using deep learning and machine learning methods
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Abstract (EN)
The Lidarseg-mini subset of the NuScenes dataset was used in the study, and the point clouds were divided into seven different classes. In the experimental studies, both classical machine learning algorithms (Random Forest, K-Nearest Neighbor, ML-MLP) and deep learning-based methods (DL-MLP, CNN, PointNet Mini) were applied, and the models were compared based on accuracy, F1, sensitivity, and precision metrics.
Author
Nisa Koban
Institution
How to Cite
Nisa Koban (Master Thesis). Classification of lidar point clouds using deep learning and machine learning methods, 2025, Karadeniz Technical University.
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