Data-Driven flood detection using neural networks
Research output: Journal contributions › Conference article in journal › Research › peer-review
Authors
This paper describes the approaches used by our team (MultiBrasil) for the Multimedia Satellite Task at MediaEval 2017. For both disaster image retrieval and flood-detection in satellite images, we employ neural networks for end-to-end learning. Specifically, for the first subtask, we exploit Convolutional Networks and Relation Networks while, for the latter, dilated Convolutional Networks were employed.
| Original language | English |
|---|---|
| Book series | CEUR Workshop Proceedings |
| Volume | 1984 |
| Number of pages | 3 |
| ISSN | 1613-0073 |
| Publication status | Published - 2017 |
| Externally published | Yes |
| Event | Multimedia Benchmark Workshop - MediaEval 2017 - Trinity College, Dublin, Ireland Duration: 13.09.2017 → 15.09.2017 http://www.multimediaeval.org/mediaeval2017/ |
- Computer Science(all)
ASJC Scopus Subject Areas
- Business informatics