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Original Article

Deep fake Face Detection Using Deep Learning

N SaiLakshmi Kumari1 P Haritha2 S Bhavitha3 P Pooja4 S S Sharmila5

1 Professor, Department of ECE, Dr. Lankapalli Bullayya College of Engineering, Visakhapatnam, Andhra Pradesh, India. *2 3 4 *5 Department of ECE, Dr. Lankapalli Bullayya College of Engineering, Visakhapatnam, Andhra Pradesh, India.

Published Online: January-April 2025

Pages: 32-33

Cite this article

↗ https://www.doi.org/10.59256/indjece.20250201001
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Abstract

Advancements in artificial intelligence (AI) have significantly enhanced the ability to generate realistic deepfake videos, raising concerns about their potential misuse in domains such as political misinformation and cybercrime. To address this issue, our research presents a deep learning-based approach utilizing LBPNET, which integrates Local Binary Patterns (LBP) with Convolutional Neural Networks (CNNs). The proposed methodology involves extracting LBP features from images, training a CNN using these features, and developing a model capable of differentiating between real and fake images. The model is rigorously tested to evaluate its effectiveness in deepfake detection.

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References

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Citations

N SaiLakshmi Kumari, P Haritha, S Bhavitha, P Pooja, S S Sharmila*, “Deep fake Face Detection Using Deep Learning”, Indian Journal of Electronics and Communication Engineering, Volume 02, Issue 01, January-April 2025, PP: 32-33

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Licensing

© 2026 The Author(s). Published by Fifth Dimension Research Publication.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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