dc.contributor.author |
Al-Mousa, Amjed |
|
dc.contributor.author |
Alzaibaq, Omar Z. |
|
dc.contributor.author |
Abu Hashyeh, Yazan K. |
|
dc.date.accessioned |
2023-05-03T12:26:49Z |
|
dc.date.available |
2023-05-03T12:26:49Z |
|
dc.date.issued |
2023-08-01 |
|
dc.identifier.issn |
2210-142X |
|
dc.identifier.uri |
https://journal.uob.edu.bh:443/handle/123456789/4896 |
|
dc.description.abstract |
In recent years, the rate of gun violence has risen at a rapid pace. Most current security systems rely on human personnel to constantly monitor lobbies and halls. With the advancement of machine learning and, specifically deep learning techniques, future closed-circuit TV (CCTV) and security systems should be able to detect threats and act upon this detection when needed.
This paper presents a security system architecture that uses deep learning and image-processing techniques for real-time weapon detection. The system relies on processing a video feed to detect people carrying different types of weapons by periodically capturing images from the video feed. These images are fed to a convolutional neural network (CNN). The CNN then decides if the image contains a threat or not. If it is a threat, it would alert the security guards on a mobile application and send them an image of the situation. The system was tested and achieved a testing accuracy of 92.5%. Also, it was able to complete the detection in as fast as 1.6 seconds. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
University of Bahrain |
en_US |
dc.subject |
CNN; Security Cameras; Weapon Detection; CCTV; Deep Learning |
en_US |
dc.title |
Deep Learning-Based Real-Time Weapon Detection System |
en_US |
dc.identifier.doi |
http://dx.doi.org/10.12785/ijcds/140141 |
|
dc.volume |
14 |
en_US |
dc.issue |
1 |
en_US |
dc.pagestart |
1 |
en_US |
dc.pageend |
1 |
en_US |
dc.contributor.authorcountry |
Jordan |
en_US |
dc.contributor.authoraffiliation |
Princess Sumaya University of Technology |
en_US |
dc.contributor.authoraffiliation |
PSUT |
en_US |
dc.contributor.authoraffiliation |
PSUT |
en_US |
dc.source.title |
International Journal of Computing and Digital Systems |
en_US |
dc.abbreviatedsourcetitle |
IJCDS |
en_US |