Artificial Intelligence and Deep Learning for Weapon Identification in Security Systems

Abstract As crime rates rise at large events and possibly lonely places, security is always a top concern in every field. A wide range of issues may be solved with the use of computer vision, including anomalous detection and monitoring. Intelligence monitoring is becoming more dependent on video surveillance systems that can recognise and analyse scene and anomaly occurrences. Using SSD and Faster RCNN techniques, this paper provides automated gun (or weapon) identification. Use of two different kinds of datasets is included in the proposed approach. As opposed to the first dataset, the second one comprises pictures that have been manually tagged. However, the trade-off between speed and precision in real-world situations determines whether or not each method will be useful.