Identification of Fake Faces Using Deep Learning

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Deepfake detection methods show promise in enhancing digital media authenticity, addressing challenges in verification.
Techniques such as convolutional neural networks and spectral feature extraction excel in image and audio processing.
Observational analysis of current methodologies reveals critical hurdles in dataset generalization and real-time capabilities.
Promising future directions aim to enhance digital content verification systems against adversarial manipulations.

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Survey highlights advances in detecting deepfakes using cnn and lstm for improved biometric verification.

K. et al. (2025) studied this question.

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