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@article{196777,
        author = {Akanksha Madwali and Sejal Pal and Prof. Sheetal Mhatre and Dr.Arundhati Niwatkar},
        title = {AI-Powered Face Recognition System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {4706-4714},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196777},
        abstract = {The increasing number of missing persons and growing security concerns in crowded public areas such as malls, fairs, concerts, and transportation hubs call for effective surveillance systems. Traditional CCTV monitoring relies heavily on manual observation, which is time-consuming and prone to mistakes. This project suggests an “AI-Powered Face Recognition System,” an automated solution that uses artificial intelligence and computer vision techniques to improve surveillance. The system keeps a database of registered individuals, including missing persons, criminals, and suspects, and continuously checks these records against faces detected in CCTV video feeds. By using deep learning methods for face detection and recognition, the system can automatically identify matches in real time. Once a match is found, the system generates alerts and provides results through a web-based dashboard interface. This enables law enforcement and security agencies to effectively monitor activities. The proposed framework aims to help locate missing persons and applies to crime prevention and security monitoring. With its combination of AI-driven facial recognition and a user- friendly interface, this project shows a scalable and practical way to tackle critical public safety issues.},
        keywords = {Artificial Intelligence, Convolutional Neural Net- work, Face Recognition in Multimedia Database, User Interface, Frames per Second (processing speed)},
        month = {April},
        }