A generalizable and accessible approach to machine learning with global satellite imagery

A generalizable and accessible approach to machine learning with global satellite imagery

This paper presents MOSAIKS, a system for planet-scale prediction of multiple outcomes using satellite imagery and machine learning (SIML). MOSAIKS generalizes across prediction domains and has the potential to enhance accessibility of SIML across research disciplines.

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Detalles Bibliográficos
Autores principales: Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Science
Q
Acceso en línea:https://doaj.org/article/35ce16c6215c446488bcca5b7caf036c
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