A benchmark dataset for binary segmentation and quantification of dust emissions from unsealed roads

The generation of reference data for machine learning models is challenging for dust emissions due to perpetually dynamic environmental conditions. We generated a new vision dataset with the goal of advancing semantic segmentation to identify and quantify vehicle-induced dust clouds from images. We...

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Detalles Bibliográficos
Autores principales: De Silva, Asanka, Ranasinghe, Rajitha, Sounthararajah, Arooran, Haghighi, Hamed, Kodikara, Jayantha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814878/
https://www.ncbi.nlm.nih.gov/pubmed/36604492
http://dx.doi.org/10.1038/s41597-022-01918-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814878/
https://www.ncbi.nlm.nih.gov/pubmed/36604492
http://dx.doi.org/10.1038/s41597-022-01918-x

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