Predicting Poverty from Satellite Imagery (2020)

2nd-year project at Télécom SudParis (2018–2019). Predicting wealth levels across African regions using satellite imagery and nighttime light intensity data. Explored CNN transfer learning, Gaussian process regression, and classical regression methods. This project was inspired by this paper

Citation: Chitturi, Varun, and Zaid Nabulsi. “Predicting poverty level from satellite imagery using deep neural networks.” arXiv preprint arXiv:2112.00011 (2021).

Image is from: here