%0 Conference Proceedings
%T Deep Learning models for passability detection of flooded roads
%A Laura Lopez-Fuentes
%A Alessandro Farasin
%A Harald Skinnemoen
%A Paolo Garza
%B MediaEval 2018 Multimedia Benchmark Workshop
%D 2018
%V 2283
%F Laura Lopez-Fuentes2018
%O LAMP; 600.084; 600.109; 600.120
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3224), last updated on Thu, 28 Mar 2019 10:34:29 +0100
%X In this paper we study and compare several approaches to detect floods and evidence for passability of roads by conventional means in Twitter. We focus on tweets containing both visual information (a picture shared by the user) and metadata, a combination of text and related extra information intrinsic to the Twitter API. This work has been done in the context of the MediaEval 2018 Multimedia Satellite Task.
%U http://refbase.cvc.uab.es/files/LFS2018.pdf