• Corpus ID: 219708523

Predicting Livelihood Indicators from Crowdsourced Street Level Images

  title={Predicting Livelihood Indicators from Crowdsourced Street Level Images},
  author={Jihyeon Janel Lee and Dylan Grosz and Sicheng Zeng and Burak Uzkent and M. Burke and D. Lobell and Stefano Ermon},
Major decisions from governments and other large organizations rely on measurements of the populace's well-being, but making such measurements at a broad scale is expensive and thus infrequent in much of the developing world. We propose an inexpensive, scalable, and interpretable approach to predict key livelihood indicators from public crowd-sourced street-level imagery. Such imagery can be cheaply collected and more frequently updated compared to traditional surveying methods, while… 
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