Arming Against Violence Yolo Based Weapon Detection

Authors

  • Mrs. Revathi Pemmaraju,N.Navya Deepthi, Manikchand Manisha, Samboju Shreya, Challa Himabindu

Keywords:

Arming Against Violence, YOLO (You Only Look Once), Weapon Detection, Computer Vision, Object Detection, Public Safety, Video Surveillance, Deep Learning, Threat Detection, Image Processing.

Abstract

The "Arming against Violence YOLO-based Weapons Detection Project" introduces a state-of-the-artsystem employing the YOLO (You Only Look Once) object detection framework to swiftly and accuratelyidentify concealed weapons in real-time. This initiative addresses the critical need for enhanced securitymeasures in public spaces, offering a proactive approach to preempting potential threats. The system's multi-object recognition capabilities enable it to simultaneously

References

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You Only Look Once: Unified, Real-Time

Object Detection. arXiv preprint arXiv:1506.02640.

Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C. Y., & Berg, A. C. (2016). SSD: Single Shot MultiBox Detector. In European conference on computer vision (pp. 21-37). Springer, Cham.

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Published

2024-05-27

How to Cite

Mrs. Revathi Pemmaraju,N.Navya Deepthi, Manikchand Manisha, Samboju Shreya, Challa Himabindu. (2024). Arming Against Violence Yolo Based Weapon Detection. Journal of Computational Analysis and Applications (JoCAAA), 33(05), 1292–1296. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2458

Issue

Section

Articles