Measuring social, environmental and health inequalities using deep learning and street imagery

Cities are home to an increasing majority of the world’s population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding urban inequalities. We applied a deep learning appro...

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Detalles Bibliográficos
Autores principales: Suel, Esra, Polak, John W., Bennett, James E., Ezzati, Majid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6473002/
https://www.ncbi.nlm.nih.gov/pubmed/31000744
http://dx.doi.org/10.1038/s41598-019-42036-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6473002/
https://www.ncbi.nlm.nih.gov/pubmed/31000744
http://dx.doi.org/10.1038/s41598-019-42036-w

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