A DEEP LEARNING FRAMEWORK FOR DETECTING FACE  SPOOFING IN BIOMETRIC AUTHENTICATION SYSTEMS

Monika ,Dr Tarun Kumar

A DEEP LEARNING FRAMEWORK FOR DETECTING FACE SPOOFING IN BIOMETRIC AUTHENTICATION SYSTEMS

Authors

Monika ,Dr Tarun Kumar

Keywords:

Abstract

The ability to detect spoofed faces has become a critical concern in various applications, such
as face recognition systems, banking, and security measures. This research presents a simple yet
effective system designed to determine

References

C. Yuan, Z. Xia, X. Sun, and Q. M. J. Wu, “Deep residual network with adaptive learning framework for fingerprint liveness detection,” IEEE Transactions on Cognitive and Developmental Systems, vol. 12, no. 3, pp. 461–473, Sep. 2020, doi: 10.1109/TCDS.2019.2920364.

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Published

2024-10-15

How to Cite

Monika ,Dr Tarun Kumar. (2024). A DEEP LEARNING FRAMEWORK FOR DETECTING FACE SPOOFING IN BIOMETRIC AUTHENTICATION SYSTEMS. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 4641–4651. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2944