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@article{169623,
        author = {Jidnesh Surve and Priti Yadav and Manas Gaikwad and Abhishek Bankar and Saurav Sawant},
        title = {Face Recognition Lock Using Siamese Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {1793-1799},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169623},
        abstract = {This research introduces an automated access control system that uses computer vision and deep learning technology to authenticate users using facial recognition. To enable precise and effective identification verification, the system uses a Siamese Neural Network architecture to compare live facial captures with reference photos that have been stored. Using deep neural networks and contemporary image processing methods, the system accomplishes reliable face detection and recognition by capturing facial features via a camera interface. The developed solution, which provides a dependable and contactless way of access management, shows how modern artificial intelligence techniques may be used practically in security system. A strong verification method that may successfully give or refuse access based on identity confirmation is produced by the Siamese Neural Network's capacity to learn discriminative features, which enables precise comparison of facial photos. This method, which combines the strength of deep learning with useful security applications, is a breakthrough in biometric security systems.},
        keywords = {Face Recognition, Siamese Neural Network, Deep Learning, Access Control, Biometric Security, Image Processing},
        month = {November},
        }