A robust deep learning approach for rock discontinuity identification from large scale 3D point clouds.

Sun J, Zhu S, Sun J, Zhou J, Yao Y, Wang Y, Zhang J, Zhou B, Wang X

Open source

DOI
10.1038/s41598-025-31137-4
Published
2025 Dec 16
Container
Scientific reports
Publisher
Not recorded
Open access
yes

Credibility signals

limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1038/s41598-025-31137-4,
  title = {A robust deep learning approach for rock discontinuity identification from large scale 3D point clouds.},
  author = {Sun J and Zhu S and Sun J and Zhou J and Yao Y and Wang Y and Zhang J and Zhou B and Wang X},
  year = {2025},
  journal = {Scientific reports},
  doi = {10.1038/s41598-025-31137-4},
  url = {https://doi.org/10.1038/s41598-025-31137-4}
}

RIS

TY  - JOUR
TI  - A robust deep learning approach for rock discontinuity identification from large scale 3D point clouds.
AU  - Sun J
AU  - Zhu S
AU  - Sun J
AU  - Zhou J
AU  - Yao Y
AU  - Wang Y
AU  - Zhang J
AU  - Zhou B
AU  - Wang X
PY  - 2025
JO  - Scientific reports
DO  - 10.1038/s41598-025-31137-4
UR  - https://doi.org/10.1038/s41598-025-31137-4
ER  - 

APA

J, S., S, Z., J, S., J, Z., Y, Y., Y, W., J, Z., B, Z., & X, W. (2025). A robust deep learning approach for rock discontinuity identification from large scale 3D point clouds.. Scientific reports. https://doi.org/10.1038/s41598-025-31137-4

Source records