Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features
2
Department of Surveying and EngineeringZhejiang Land Surveying and Planning Co. Ltd, Hangzhou, People’s Republic of China
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Publication type: Journal Article
Publication date: 2022-02-01
scimago Q2
wos Q3
SJR: 0.676
CiteScore: 5.9
Impact factor: 2.6
ISSN: 01431161, 13665901
General Earth and Planetary Sciences
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Metrics
14
Total citations:
14
Citations from 2024:
7
(50%)
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MLA
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GOST
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Wang Y. et al. Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features // International Journal of Remote Sensing. 2022. Vol. 43. No. 3. pp. 932-960.
GOST all authors (up to 50)
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Wang Y., Zhou T., Li H., Li H., Tu W., Xi J., Liao L. Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features // International Journal of Remote Sensing. 2022. Vol. 43. No. 3. pp. 932-960.
Cite this
RIS
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TY - JOUR
DO - 10.1080/01431161.2021.2022242
UR - https://doi.org/10.1080/01431161.2021.2022242
TI - Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features
T2 - International Journal of Remote Sensing
AU - Wang, Yongzhi
AU - Zhou, Tao
AU - Li, Hui
AU - Li, Hongdong
AU - Tu, Wenlong
AU - Xi, Jing
AU - Liao, Lixia
PY - 2022
DA - 2022/02/01
PB - Taylor & Francis
SP - 932-960
IS - 3
VL - 43
SN - 0143-1161
SN - 1366-5901
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2022_Wang,
author = {Yongzhi Wang and Tao Zhou and Hui Li and Hongdong Li and Wenlong Tu and Jing Xi and Lixia Liao},
title = {Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features},
journal = {International Journal of Remote Sensing},
year = {2022},
volume = {43},
publisher = {Taylor & Francis},
month = {feb},
url = {https://doi.org/10.1080/01431161.2021.2022242},
number = {3},
pages = {932--960},
doi = {10.1080/01431161.2021.2022242}
}
Cite this
MLA
Copy
Wang, Yongzhi, et al. “Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features.” International Journal of Remote Sensing, vol. 43, no. 3, Feb. 2022, pp. 932-960. https://doi.org/10.1080/01431161.2021.2022242.