The Increasing Crime Rate In Crowded Events Or Isolated Areas Has Heightened The Importance Of Security Across All Domains. Computer Vision Has Significant Applications In Addressing A Range Of Problems Through The Identification And Surveillance Of Abnormalities. The Increasing Need To Protect Safety, Security, And Personal Belongings Has Led To A Significant Demand For Video Surveillance Systems Capable Of Recognizing And Interpreting Scenes As Well As Detecting Unusual Events. These Systems Play A Crucial Role In Intelligent Monitoring. This Research Paper Applies Convolutional Neural Network (CNN) Based SSD And Faster RCNN Algorithms To Achieve Automatic Detection Of Guns Or Weapons. The Suggested Approach Entails The Utilization Of Two Distinct Categories Of Datasets. One Dataset Containing Pre-labeled Images.
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