Browse wiki
From ISLAB/CAISR
| Name of the new projectEstimating agricultural development indicators over large areas from satellite images – an approach using convolutional neural networks and transfer learning |
| Level | Master + |
|---|---|
| OneLineSummary | In this project you will use deep learning models, specifically convolutional neural networks (CNN), to analyze satellite imagery to estimate agricultural development indicators. + |
| Prerequisites | Good knowledge of machine learning, convolutional neural networks and programming skills for implementing machine learning algorithms + |
| References | Xie, M., N. Jean, M. Burke, D. Lobell & … Xie, M., N. Jean, M. Burke, D. Lobell & S. Ermon (2015) Transfer learning from deep features for remote sensing and poverty mapping. arXiv preprint arXiv:1510.00098. Jean, N., M. Burke, et al (2016) Combining satellite imagery and machine learning to predict poverty. Science, 353, 790-794.to predict poverty. Science, 353, 790-794. |
| StudentProjectStatus | Open + |
| Supervisors | Mattias Ohlsson + , Thorsteinn Rögnvaldsson + |
| TimeFrame | Fall 2019 + |
| Title | Name of the new projectEstimating agricultural development indicators over large areas from satellite images – an approach using convolutional neural networks and transfer learning + |
| Categories | StudentProject + |
| Modification dateThis property is a special property in this wiki. | 1 October 2019 07:41:18 + |
| hide properties that link here |
| No properties link to this page. |
