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Author Xukun Li; Doina Caragea; Cornelia Caragea; Muhammad Imran; Ferda Ofli pdf  isbn
openurl 
  Title Identifying Disaster Damage Images Using a Domain Adaptation Approach Type Conference Article
  Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019  
  Volume Issue Pages  
  Keywords image classification, disaster damage, domain adaptation, domain adversarial neural networks.  
  Abstract Approaches for effectively filtering useful situational awareness information posted by eyewitnesses of disasters,

in real time, are greatly needed. While many studies have focused on filtering textual information, the research

on filtering disaster images is more limited. In particular, there are no studies on the applicability of domain

adaptation to filter images from an emergent target disaster, when no labeled data is available for the target disaster.

To fill in this gap, we propose to apply a domain adaptation approach, called domain adversarial neural networks

(DANN), to the task of identifying images that show damage. The DANN approach has VGG-19 as its backbone,

and uses the adversarial training to find a transformation that makes the source and target data indistinguishable.

Experimental results on several pairs of disasters suggest that the DANN model generally gives similar or better

results as compared to the VGG-19 model fine-tuned on the source labeled data.
 
  Address Department of Computer Science, Kansas State University, United States of America;Department of Computer Science, University of Illinois at Chicago, United States of America;Qatar Computing Research Institute, Hamad Bin Khalifa University, Qatar  
  Corporate Author Thesis  
  Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium  
  Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)  
  Notes Approved no  
  Call Number Serial (down) 1853  
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Author Thomas Spielhofer; Anna Sophie Hahne; Christian Reuter; Marc-André Kaufhold; Stefka Schmid pdf  isbn
openurl 
  Title Social Media Use in Emergencies of Citizens in the United Kingdom Type Conference Article
  Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019  
  Volume Issue Pages  
  Keywords Emergencies; social media; Twitter; Facebook; representative study  
  Abstract People use social media in various ways including looking for or sharing information during crises or emergencies

(e.g. floods, storms, terrorist attacks). Few studies have focused on European citizens? perceptions, and just one

has deployed a representative sample to examine this. This article presents the results of one of the first

representative studies on this topic conducted in the United Kingdom. The study shows that around a third (34%)

have used social media during an emergency and that such use is more widespread among younger people. In

contrast, the main reasons for not using social media in an emergency include technological concerns and that the

trustworthiness of social media content is doubtful. However, there is a growing trend towards increased use. The

article deduces and explores implications of these findings, including problems potentially arising with more

citizens sharing information on social media during emergencies and expecting a response.
 
  Address Technische Universität Darmstadt, Science and Technology for Peace and Security (PEASEC), Germany;The Tavistock Institute of Human Relations (TIHR)  
  Corporate Author Thesis  
  Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium  
  Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)  
  Notes Approved no  
  Call Number Serial (down) 1849  
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