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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM16064
Volume:
6 |
8 |
Aug 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The component of a computer system that is in charge of user security is one of the most crucial ones. Simple logins and passwords have been shown to be vulnerable to hackers and unable to provide high levels of efficiency. The most common replacements is identity recognition using biometrics. The use of the iris as a biometric feature has gained popularity in recent years. It resulted from the exceptional efficiency and precision that this approach provided. The results of this interest may be seen in the literature. Various authors have put forward a variety of various methods. The authors of this paper describe their own method for an iris-based algorithm for recognizing human identification. Artificial neural networks and a CNN-based transfer learning model (Mobile Net) were employed in the classification process. As soon as the classification is complete, the iris section is segmented on the result of the classification. The proposed approach can produce results that are adequate, according to tests that have been run.
KEYWORDS
Publication Date
4/22/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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