Refined DHS targets, two-stage image-quality screening, and spherical-harmonic geo-encoding reduce KidSat MAE from 0.2167 to 0.1759 (18.83 percent relative) and reach 0.1658 on 33 African countries.
Combining satellite imagery and machine learning to predict poverty.Science, 353(6301):790–794, 2016
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Enhancing the KidSat Model: Integrating Geographical Encoding and Data Quality Assessment for Childhood Poverty Prediction
Refined DHS targets, two-stage image-quality screening, and spherical-harmonic geo-encoding reduce KidSat MAE from 0.2167 to 0.1759 (18.83 percent relative) and reach 0.1658 on 33 African countries.