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Detection of Flooding Events in Social Multimedia and Satellite Imagery using Deep Neural Networks

Benjamin Bischke; Prakriti Bhardwaj; Aman Gautam; Patrick Helber; Damian Borth; Andreas Dengel
In: Working Notes Proceedings of the MediaEval 2017. MediaEval Benchmark, September 13-15, Dublin, Ireland, MediaEval, 2017.


This paper presents the solution of the DFKI-team for the Multimedia Satellite Task at MediaEval 2017. In our approach, we strongly relied on deep neural networks. The results show that the fusion of visual and textual features extracted by deep networks can be effectively used to retrieve social multimedia reports which provide a directed evidence of flooding. Additionally, we extend existing net- work architectures for semantic segmentation to incorporate RGB and Infrared (IR) channels into the model. Our results show that IR information is of vital importance for the detection of flooded areas in satellite imagery.