Using publicly available satellite imagery and deep learning to understand economic well-being in Africa
It is generally difficult to scale derived estimates and understand the accuracy across locations for passively-collected data sources, such as mobile phones and satellite imagery. Here the authors show that their trained deep learning models are able to explain 70% of the variation in ground-measur...
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Autores principales: | Christopher Yeh, Anthony Perez, Anne Driscoll, George Azzari, Zhongyi Tang, David Lobell, Stefano Ermon, Marshall Burke |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2020
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Materias: | |
Acceso en línea: | https://doaj.org/article/7795998e04994473a909cfaf24b6daf9 |
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