Weapon Detection System Using Deep Learning
Author(s):
P Murugan, A Merry Ida, S.Amshiga Brillian, M.Seals Ancy, R Aashika, S.Sneha
Keywords:
Computer vision, weapon detection, Faster RCNN, CCTV, Machine learning (MI)
Abstract
Weapon detection is a crucial task in ensuring public safety and preventing violent incidents. In recent years, computer vision technology has been used for real- time weapon detection, and the YOLO (You Only Look Once) object detection algorithm has emerged as a popular and efficient technique for this purpose. In this report, we discuss the use of YOLO for weapon detection, and its performance in identifying firearms, knives, and other weapons. We trained a YOLOv8 model using a dataset of annotated images, and evaluated its performance on a test dataset. The results indicate that YOLO is an accurate and efficient technique for weapon detection, achieving a high map and mA it improves the performance of the model in different scenarios.
Article Details
Unique Paper ID: 160929

Publication Volume & Issue: Volume 10, Issue 2

Page(s): 104 - 109
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