Multiclass Weapon Detection using Multi Contrast Convolutional Neural Networks and Faster Region-Based Convolutional Neural Networks
Rahul Reddy, K Gyan Vallabh, Sai Sharan · 2021 2nd International Conference for Emerging Technology (INCET) · 2021
In this day and age, increasingly easy access to firearms and other hand-held weapons has stirred up public violence concerns. Many of these weapons are comfortably concealed. The tremendous developments in technology can assure more security in public places by detecting such weapons in real-time and alerting the concerned authorities before any damage. In this paper, we propose using two state-of-the-art algorithms for performing real-time detection of concealed hand-held weapons. The algorithms used are Multi Contrast Convolutional Neural Networks (MC-CNN) and Faster Region-Based Convolutional Neural Networks (Faster R-CNN). Additionally, we present a comprehensive comparative analysis and evaluation of the Faster R-CNN and MC-CNN in detecting the weapons. This study has diverse industrial applications in real-time bank surveillance cameras and other public places, provided that they are under CCTV surveillance.