Predicting bilgewater emulsion stability by oil separation using image processing and machine learning
- DOI
- 10.1016/j.watres.2022.118977
- Published
- 2022-09
- Container
- Water Research
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.watres.2022.118977,
title = {Predicting bilgewater emulsion stability by oil separation using image processing and machine learning},
author = {Woo Hyoung Lee and Cheol Young Park and Daniela Diaz and Kelsey L. Rodriguez and Jongik Chung and Jared Church and Marjorie R. Willner and Jeffrey G. Lundin and Danielle M. Paynter},
year = {2022},
journal = {Water Research},
doi = {10.1016/j.watres.2022.118977},
url = {https://doi.org/10.1016/j.watres.2022.118977}
}RIS
TY - JOUR TI - Predicting bilgewater emulsion stability by oil separation using image processing and machine learning AU - Woo Hyoung Lee AU - Cheol Young Park AU - Daniela Diaz AU - Kelsey L. Rodriguez AU - Jongik Chung AU - Jared Church AU - Marjorie R. Willner AU - Jeffrey G. Lundin AU - Danielle M. Paynter PY - 2022 JO - Water Research DO - 10.1016/j.watres.2022.118977 UR - https://doi.org/10.1016/j.watres.2022.118977 ER -
APA
Lee, W. H., Park, C. Y., Diaz, D., Rodriguez, K. L., Chung, J., Church, J., Willner, M. R., Lundin, J. G., & Paynter, D. M. (2022). Predicting bilgewater emulsion stability by oil separation using image processing and machine learning. Water Research. https://doi.org/10.1016/j.watres.2022.118977
Source records
- crossref · retrieved 2026-09-26T23:35:49.909Z