Multimodal deep learning from satellite and street-level imagery for measuring income, overcrowding, and environmental deprivation in urban areas

Data collected at large scale and low cost (e.g. satellite and street level imagery) have the potential to substantially improve resolution, spatial coverage, and temporal frequency of measurement of urban inequalities. Multiple types of data from different sources are often available for a given ge...

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Detalles Bibliográficos
Autores principales: Suel, Esra, Bhatt, Samir, Brauer, Michael, Flaxman, Seth, Ezzati, Majid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Elsevier Pub. Co 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985619/
https://www.ncbi.nlm.nih.gov/pubmed/33941991
http://dx.doi.org/10.1016/j.rse.2021.112339

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985619/
https://www.ncbi.nlm.nih.gov/pubmed/33941991
http://dx.doi.org/10.1016/j.rse.2021.112339

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