Browse wiki
From ISLAB/CAISR
| Explainable AI and poverty prediction |
| Keywords | Satellite data, transfer learning, explainable AI, Africa, economic development indicators + |
|---|---|
| Level | Master + |
| OneLineSummary | Provide explanations of AI data-driven poverty predictions in sub-saharan africa + |
| Prerequisites | Machine learning, deep learning + |
| References | (1) Lee and Braithwaite (2021), "High-Reso … (1) Lee and Braithwaite (2021), "High-Resolution Poverty Maps in Sub-Saharan Africa", https://arxiv.org/abs/2009.00544 (2) Jean, Burke, Xie, Davis, Lobell, and Ermon (2016), "Combining satellite imagery and machine learning to predict poverty", Science, https://www.science.org/doi/10.1126/science.aaf7894 (3) Roscher, Bohn, Duarte, and Garcke (2020), "Explainable Machine Learning for Scientific Insights and Discoveries", IEEE Access, https://ieeexplore.ieee.org/document/9007737tps://ieeexplore.ieee.org/document/9007737 |
| StudentProjectStatus | Open + |
| Supervisors | Thorsteinn Rögnvaldsson + , Mattias Ohlsson + |
| TimeFrame | Fall 2022 + |
| Title | Explainable AI and poverty prediction + |
| Categories | StudentProject + |
| Modification dateThis property is a special property in this wiki. | 10 October 2022 20:32:24 + |
| hide properties that link here |
| No properties link to this page. |
