Improving corrosion depth estimation in buried pipelines using SMOTE-integrated machine and deep learning models.

AlOmar MK, Hameed MM, Ali OK, Samir AA, Kukreja T, Masood A, Salem A

DOI: 10.1371/journal.pone.0355187
Published: 2026
Container: PloS one
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0355187,
  title = {Improving corrosion depth estimation in buried pipelines using SMOTE-integrated machine and deep learning models.},
  author = {AlOmar MK and Hameed MM and Ali OK and Samir AA and Kukreja T and Masood A and Salem A},
  year = {2026},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0355187},
  url = {https://doi.org/10.1371/journal.pone.0355187}
}

RIS

TY  - JOUR
TI  - Improving corrosion depth estimation in buried pipelines using SMOTE-integrated machine and deep learning models.
AU  - AlOmar MK
AU  - Hameed MM
AU  - Ali OK
AU  - Samir AA
AU  - Kukreja T
AU  - Masood A
AU  - Salem A
PY  - 2026
JO  - PloS one
DO  - 10.1371/journal.pone.0355187
UR  - https://doi.org/10.1371/journal.pone.0355187
ER  -

APA

MK, A., MM, H., OK, A., AA, S., T, K., A, M., & A, S. (2026). Improving corrosion depth estimation in buried pipelines using SMOTE-integrated machine and deep learning models.. PloS one. https://doi.org/10.1371/journal.pone.0355187

Source records

pubmed · retrieved 2026-09-25T08:54:06.284Z