@inproceedings{2dec98cffe1341558a95d830f2c0b3cf,
title = "Directed Point Clouds Denoising Algorithm Based on Self-learning",
abstract = "Traditional statistical scan cleaning methods usually make assumptions about the scanned surfaces or noise model, which requires users to manually adjust the settings. The learning-based method needs a data set for training, and the denoising effect of objects outside the data set is general. A self-learning directed point cloud denoising algorithm has been proposed. By introducing the self-learning method without pre training, this method makes denoising and gridding promote each other, and achieves good denoising effect. Our method does not require pretraining or preset parameters and has a good denoising effect on various noises.",
keywords = "Point-cloud denoising, Self-learning",
author = "Yijie Fan and Linlin Tang and Yang Liu and Shuhan Qi",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 5th International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2022 ; Conference date: 24-12-2022 Through 26-12-2022",
year = "2023",
doi = "10.1007/978-981-99-0848-6\_29",
language = "英语",
isbn = "9789819908479",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "373--383",
editor = "Shaoquan Ni and Tsu-Yang Wu and Jingchun Geng and Shu-Chuan Chu and Tsihrintzis, \{George A.\}",
booktitle = "Advances in Smart Vehicular Technology, Transportation, Communication and Applications - Proceedings of VTCA 2022",
address = "德国",
}