Enhancing a Real-time Face Recognition Accuracy With Innovative using Convolutional Neural Networks

Abstract

Abstract This paper introduces an innovative facial recognition criminal detection system that is at the forefront of technology. Its primary goal is to identify suspects in real-time, using cutting-edge algorithms and live camera technology. By combining these advanced features, the system significantly enhances security measures and helps combat criminal activities. Facial recognition has become a prominent tool in the field of security, revolutionizing surveillance for threat detection. The user-friendly desktop application offers a wide range of features, including the ability to view crime statistics and upload suspect images. With an impressive accuracy rate of 99.38%, the system excels at identifying potential criminals, thanks to its integration with live camera sensors. Administrators benefit from additional privileges, such as direct management of the suspect database, user account control, and system monitoring. An admin dashboard provides efficient oversight of suspects, approval requests, and user management, enabling effective decision-making.