Continuous monitoring of suspended sediment concentrations using image analytics and deriving inherent correlations by machine learning

The barriers for the development of continuous monitoring of Suspended Sediment Concentration (SSC) in channels/rivers include costs and technological gaps but this paper shows that a solution is feasible by: (i) using readily available high-resolution images; (ii) transforming the images into image...

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Detalles Bibliográficos
Autores principales: Ghorbani, Mohammad Ali, Khatibi, Rahman, Singh, Vijay P., Kahya, Ercan, Ruskeepää, Heikki, Saggi, Mandeep Kaur, Sivakumar, Bellie, Kim, Sungwon, Salmasi, Farzin, Hasanpour Kashani, Mahsa, Samadianfard, Saeed, Shahabi, Mahmood, Jani, Rasoul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244478/
https://www.ncbi.nlm.nih.gov/pubmed/32444611
http://dx.doi.org/10.1038/s41598-020-64707-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244478/
https://www.ncbi.nlm.nih.gov/pubmed/32444611
http://dx.doi.org/10.1038/s41598-020-64707-9

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