2 citations · 2 across the 4 of their papers we have counts for
5 papers
Poverty rate prediction using multi-modal survey and earth observation data
Simone Fobi, Manuel Cardona, Elliott Collins +5
This work presents an approach for combining household demographic and living standards survey questions with features derived from satellite imagery to predict the poverty rate of…
Proceedings of the NeurIPS 2021 Workshop on Machine Learning for the Developing World: Global Challenges
Paula Rodriguez Diaz, Tejumade Afonja, Konstantin Klemmer +4
These are the proceedings of the 5th workshop on Machine Learning for the Developing World (ML4D), held as part of the Thirty-fifth Conference on Neural Information Processing Syst…
A Higher Purpose: Measuring Electricity Access Using High-Resolution Daytime Satellite Imagery
Zeal Shah, Simone Fobi, Gabriel Cadamuro +1
Governments and international organizations the world over are investing towards the goal of achieving universal energy access for improving socio-economic development. However, in…
Predicting Levels of Household Electricity Consumption in Low-Access Settings
Simone Fobi, Joel Mugyenyi, Nathaniel J. Williams +2
In low-income settings, the most critical piece of information for electric utilities is the anticipated consumption of a customer. Electricity consumption assessment is difficult…
Learning to segment from misaligned and partial labels
Simone Fobi, Terence Conlon, Jayant Taneja +1
To extract information at scale, researchers increasingly apply semantic segmentation techniques to remotely-sensed imagery. While fully-supervised learning enables accurate pixel-…