A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery

no code implementations • 16 Oct 2020 • Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang

Combining satellite imagery with machine learning (SIML) has the potential to address global challenges by remotely estimating socioeconomic and environmental conditions in data-poor regions, yet the resource requirements of SIML limit its accessibility and use.

BIG-bench Machine Learning regression +1