Purpose
to improve food security in low-resource settings by testing whether synthetic imaging data can replace ground reference data, which is difficult to collect, train machine learning algorithms better classify crop types from satellite images
Grantee
Division
Global Health
Date
APRIL 2020
Region served
GLOBAL
Committed amount
$200,000
Grant topic
Discovery and Translational Sciences
Duration (months)
24
Grantee location
Washington, District of Columbia, United States
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