1 AIML Department, Aditya University, Surampalem. India.
2 Physics Department, School of Physical Sciences and Engineering, Manipur International University, Imphal.
3 Department of Computer Science, School of Physical Sciences and Engineering, Manipur International University, Imphal.
4 C and IT Department, J.N.N. Institute of Engineering, Chennai, India.
International Journal of Science and Research Archive, 2026, 18(02), 656-659
Article DOI: 10.30574/ijsra.2026.18.2.0318
Received on 09 January 2026; revised on 16 February 2026; accepted on 18 February 2026
Facial recognition is grasping a lot of buzz these days because it can be used in security, access control, surveillance, and making sure someone is who they say they are. This research shows a better way to recognize faces using a Deep Face network, which was created to pull out better features and classify them more accurately. The idea is an integration of transfer learning and deep residual learning to get best feature extraction and recognition rate, even in different lightning conditions and pose variations. Deep face network was deployed with one million labelled faces of Image Net. The Deep Face network provides better in accuracy than traditional methods and Results shows that the deep face model is better in real-world uses in security and authenticity.
Convolutional Neural Networks; Deep Face; Deep Learning; Transfer Learning; Facial Key Points
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Tadi Chandrasekhar, Th. Basanta, Mutum.Bidyarani Devi and J.N. Swaminathan. Face recognition using deep face. International Journal of Science and Research Archive, 2026, 18(02), 656-659. Article DOI: https://doi.org/10.30574/ijsra.2026.18.2.0318.
Copyright © 2026 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
