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@article{193099,
        author = {Shraddha Navnath Phad and Shital Anil mengal and Sanskruti Sunil Gangurde and Dhanashri Kisan Jadhav and Aishwarya Sanjay Sanap and M. P. Bhandakkar},
        title = {Secure And Hassle Free EVM through Deep Learning Base Face Recognition},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {4085-4089},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193099},
        abstract = {security, reduces manual intervention, election and increases public trust in the voting process. The solution is suitable for small-scale elections, institutional voting, and future smart governance applications. The Smart Electronic Voting Machine (EVM) using Facial Recognition improves is an intelligent and secure voting solution designed to enhance the integrity and transparency of the electoral process. The system integrates machine learning–based facial recognition techniques with electronic voting to ensure accurate voter authentication and prevent multiple voting by the same individual. A camera module captures the voter’s facial image, which is processed using face recognition algorithms and compared with pre-registered voter data stored in the system.
The primary objective of the system is to eliminate voter impersonation, reduce election fraud, and enforce the principle of “one person, one vote.” Once a voter’s identity is successfully verified, the voting option is enabled. After the vote is cast, the system locks the voter’s identity to prevent repeated voting attempts. All voting data is securely stored for counting and verification purposes.
By combining biometric authentication with electronic voting, the proposed system.},
        keywords = {Smart EVM, Facial Recognition, Machine Learning, Biometric Authentication, Secure Voting System.},
        month = {February},
        }