Comparative Analysis on Different DeepFake Detection Methods and Semi Supervised GAN Architecture for DeepFake Detection

Author:

John Jerry1,Sherif Bismin V.1

Affiliation:

1. Muthoot Institute Of Technology And Science,Kochi,India

Publisher

IEEE

Reference20 articles.

1. FPGAN: Face de-identification method with generative adversarial networks for social robots

2. Protecting world leaders against deep fakes;agarwal;Computer Vision and Pattern Recognition Workshop,2019

3. Deepfake Detection Using Multiple Data Modalities

4. Self-attention generative adversarial networks;zhang;arXiv preprint arXiv 1805 08318,2018

5. Construction of Hybrid Deep Learning Model for Predicting Children Behavior based on their Emotional Reaction;kumar;Journal of Information Technology,2021

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1. Unmasking deepfakes: A systematic review of deepfake detection and generation techniques using artificial intelligence;Expert Systems with Applications;2024-10

2. Deepfake Image Forgery Detection for Suspicious Images;Lecture Notes in Networks and Systems;2024

3. Autonomous Detection and Evaluation of Deepfakes: A Comprehensive Study;2023 Seventh International Conference on Image Information Processing (ICIIP);2023-11-22

4. Detecting Deepfake Human Face Images Using Transfer Learning: A Comparative Study;2023 IEEE International Conference on Contemporary Computing and Communications (InC4);2023-04-21

5. Anti-Compression Contrastive Facial Forgery Detection;IEEE Transactions on Multimedia;2023

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