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Author  |
Dat T. Nguyen; Firoj Alam; Ferda Ofli; Muhammad Imran |
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Title |
Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises |
Type |
Conference Article |
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Year |
2017 |
Publication |
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2017 |
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Volume |
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Pages |
499-511 |
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Keywords |
social media; image processing; supervised classification; disaster management |
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Abstract |
The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly. In addition to the textual content, people post overwhelming amounts of imagery data on social networks within minutes of a disaster hit. Studies point to the importance of this online imagery content for emergency response. Despite recent advances in the computer vision field, automatic processing of the crisis-related social media imagery data remains a challenging task. It is because a majority of which consists of redundant and irrelevant content. In this paper, we present an image processing pipeline that comprises de-duplication and relevancy filtering mechanisms to collect and filter social media image content in real-time during a crisis event. Results obtained from extensive experiments on real-world crisis datasets demonstrate the significance of the proposed pipeline for optimal utilization of both human and machine computing resources. |
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Address |
Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar |
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Publisher |
Iscram |
Place of Publication |
Albi, France |
Editor |
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Series Volume |
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Edition |
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ISSN |
2411-3387 |
ISBN |
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Track |
Social Media Studies |
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Conference |
14th International Conference on Information Systems for Crisis Response And Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2038 |
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