Anastasia Moumtzidou
Panagiotis Giannakeris
Stelios Andreadis
Athanasios Mavropoulos
Georgios Meditskos
Ilias Gialampoukidis
Konstantinos Avgerinakis
Stefanos Vrochidis
Ioannis Kompatsiaris
2018-10-29
<p>This paper presents the algorithms that CERTH-ITI team deployed so as to deal with flood detection and road passability from social media and satellite data. Computer vision and deep learning techniques are combined so as to analyze social media and satellite images, while word2vec is used to analyze textual data. Multimodal fusion is also deployed in CERTH-ITI framework, both in early and late stage, by combining deep representation features in the former and semantic logic in the latter so as to provide a deeper and more meaningful understanding of the flood events.</p>
https://doi.org/10.5281/zenodo.2540398
oai:zenodo.org:2540398
Zenodo
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.2540397
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
MediaEval 2018 Workshop, 29-31 October 2018
A multimodal approach in estimating road passability through a flooded area using social media and satellite images
info:eu-repo/semantics/conferencePaper