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.

Bibliographic Details
Main Authors: Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang
Format: Article
Language:English
Published: Nature Publishing Group 2021-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-24638-z

Internet

https://doi.org/10.1038/s41467-021-24638-z

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