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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2019
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| Materias: | |
| 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 |