TY  - CONF
AU  - Laura Lopez-Fuentes
AU  - Alessandro Farasin
AU  - Harald Skinnemoen
AU  - Paolo Garza
A2  - MediaEval
PY  - 2018//
TI  - Deep Learning models for passability detection of flooded roads
BT  - MediaEval 2018 Multimedia Benchmark Workshop
VL  - 2283
N2  - 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.
L1  - http://refbase.cvc.uab.es/files/LFS2018.pdf
N1  - LAMP; 600.084; 600.109; 600.120
ID  - Laura Lopez-Fuentes2018
ER  -