| Records |
| Author |
Hussein Mouzannar; Yara Rizk; Mariette Awad |
| Title |
Damage Identification in Social Media Posts using Multimodal Deep Learning |
Type |
Conference Article |
| Year |
2018 |
Publication |
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2018 |
| Volume |
|
Issue |
|
Pages |
529-543 |
| Keywords |
Humanitarian computing, deep neural networks, multimodal learning, natural language processing, visual object recognition. |
| Abstract |
Social media has recently become a digital lifeline used to relay information and locate survivors in disaster situations. Currently, officials and volunteers scour social media for any valuable information; however, this approach is implausible as millions of posts are shared by the minute. Our goal is to automate actionable information extraction from social media posts to efficiently direct relief resources. Identifying damage and human casualties allows first responders to efficiently allocate resources and save as many lives as possible. Since social media posts contain text, images and videos, we propose a multimodal deep learning framework to identify damage related information. This framework combines multiple pretrained unimodal convolutional neural networks that extract features from raw text and images independently, before a final classifier labels the posts based on both modalities. Experiments on a home-grown database of labeled social media posts showed promising results and validated the merits of the proposed approach. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
|
| Track |
Social Media Studies |
Expedition |
|
Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
2129 |
| Share this record to Facebook |
| |
|
| |
| Author |
Leon J.M. Rothkrantz |
| Title |
Crisis management using multiple camera surveillance systems |
Type |
Conference Article |
| Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
| Volume |
|
Issue |
|
Pages |
617-626 |
| Keywords |
Disasters; Information systems; Object recognition; Crisis management; License plate recognition; Multiple cameras; Semi-automatics; Surveillance systems; Tracking algorithm; Video surveillance; Video surveillance systems; Security systems |
| Abstract |
During recent disasters such as tsunami, flooding, hurricanes, nuclear disaster, earthquake people have to leave their living areas for their own safety. But it proves that some people are not informed about the evacuation, or are not willing or able to leave or don't know how to leave the hazardous areas. The topic of the paper is how to adapt current video surveillance systems along highway and streets to semi-automatic surveillance systems. When a suspicious event is detected a human operator in the control room has to be alerted to take appropriate actions. The architecture of the system and main modules are presented in the paper. Different algorithms to detect localize and track people are published by the authors elsewhere but are summarized in the current paper. The system has been tested in a real life environment and the test results are presented in the paper. |
| Address |
Delft University of Technology, Netherlands Defense Academy, Netherlands |
| Corporate Author |
|
Thesis |
|
| Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
|
| Track |
Intelligent Systems |
Expedition |
|
Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
892 |
| Share this record to Facebook |
