CLASSIFICATION OF POINT CLOUD USING DEEP LEARNING
DOI:
https://doi.org/10.24867/27KG02JankovicKeywords:
point cloud, LiDAR, deep learning, ANN, classification, Python, object detectionAbstract
This paper describes the process of creating a model of artificial neural network in order to classify point cloud. The model is trained with different input parameters and then tested with different metrics.
References
[1] Saifullahi A. B., Shangshu Y., Cheng W., Jibril M.A., Jonathan L., “Review: Deep Learning on 3D Point Clouds”
[2] Bayu A., Wibisono A., Wisesa H. A., Intizhami N. S., Jatmiko W., Gamal A., “Semantic Segmentation of Lidar Point Cloud in Rural Area”, 2019 IEEE International Conference on Communication, Networks and Satellite
[3] https://www.simplilearn.com/data-preprocessing-in-machine-learning-article (приступљено у октобру 2023.)
[2] Bayu A., Wibisono A., Wisesa H. A., Intizhami N. S., Jatmiko W., Gamal A., “Semantic Segmentation of Lidar Point Cloud in Rural Area”, 2019 IEEE International Conference on Communication, Networks and Satellite
[3] https://www.simplilearn.com/data-preprocessing-in-machine-learning-article (приступљено у октобру 2023.)
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Published
2024-08-05
Issue
Section
Geodesy Engineering
