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Author (up) Laura Lopez-Fuentes; Alessandro Farasin; Harald Skinnemoen; Paolo Garza edit   pdf
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  Title Deep Learning models for passability detection of flooded roads Type Conference Article
  Year 2018 Publication MediaEval 2018 Multimedia Benchmark Workshop Abbreviated Journal  
  Volume 2283 Issue Pages  
  Keywords  
  Abstract 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.  
  Address Sophia Antipolis; France; October 2018  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
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  ISSN ISBN Medium  
  Area Expedition Conference MediaEval  
  Notes LAMP; 600.084; 600.109; 600.120 Approved no  
  Call Number Admin @ si @ LFS2018 Serial 3224  
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