Data-Driven Flood Detection using Neural Networks
Published in Working Notes Proc. MediaEval Workshop, 2017
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.
Recommended citation: K. Nogueira, S. G. Fadel, Í. C. Dourado, R. de O. Werneck, J. A.V. Muñoz, O. A.B. Penatti, R. T. Calumby, L. T. Li, J. A. dos Santos, and R. da S. Torres. Data-Driven Flood Detection using Neural Networks. In Working Notes Proc. MediaEval Workshop, 2017.
DOI | Download Paper | Download Bibtex