Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{151873,
        author = {Yatin Misra and Zeeshan Basheer and Zakir Subzar and Sambhav},
        title = {Face Recognition},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {1121-1123},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151873},
        abstract = {Wouldn’t you're keen on to exchange password-based access control to avoid to reset forgotten password and worry about the integrity of your system? Wouldn’t you wish to rest secure in comfort that your healthcare system doesn't merely on your Social Security number as proof of your identity for granting the entry to your medical records? Because each of those questions is becoming more and more important, access to a reliable personal identification has been becoming increasingly essential. Conventional method of identification based on possession of ID cards or exclusive knowledge sort of a Social Security number or a password are not all together reliable. ID cards can be lost forged or misplaced; passwords can be forgotten or compromised. But a face is undeniably connected to its owner. It cannot be borrowed stolen or easily forged. Face recognition technology will solve this problem since a face is undeniably connected to its owner expect within the case of identical twins. It’s non-transferable. The system can then compare scans to records stored during a central or local database or maybe on a sensible card.},
        keywords = {Computer Vision, Deep Learning, Face Recognition},
        month = {},
        }