Artificial Intelligence–Based Detection of Deepfake Media on Social Platforms: Evaluating Machine Learning Models for Identifying Manipulated Video Content
A critical narrative review of deepfake detection research, comparing traditional forensic methods, classical machine learning approaches, and contemporary deep learning systems concludes that deep learning provides the strongest current detection capability, but no single architecture is sufficiently general, explainable, efficient, and robust for universal deployment.
This study uses ResNet-50 architecture, a well-known Convolutional Neural Network model, to identify tampered videos using DL, and indicates that the proposed model works effectively compared to existing deepfake methods.
Iftikhar Alam, Malik Ahsan Kamran, Ehaab Ullah· The International Journal of...· 0 citations
It is concluded that effective deepfake governance requires defense in depth integrating forensic detection, verifiable provenance, and institutional accountability.
A novel DeepFake detection technique that utilizes lightweight CNN architectures, such as MesoNet and MobileNet, coupled with an LSTM, and is subsequently fine-tuned to detect deepfakes, demonstrating notable efficiency in deepfake detection.
Padmalaya Nayak, B. Vaishnavi, L. K. Suresh Kumar· Multimedia tools and applica...· 0 citations
The authors suggest a computationally efficient multimodal deep learning framework using Bidirectional Encoder Representations of Transformers (BERT) to extract textual features and convolutional neural networks to learn visual representations that offers a computational scaling alternative to attention-based models, w...
P. Jadhav, R. K. Shukla· International Research Journ...· 0 citations
This research presents a dual model system integrating machine learning-based user verification with deep learning-based content analysis to detect fraudulent activity more effectively than traditional single dimensional approaches.
B. Bokolo, Qingzhong Liu· Electronics· 0 citations
Misinformation propagation across online platforms continues to pose serious risks to informed public discourse and media credibility. To address this, we design and evaluate a fully integrated fake news detection pipeline built upon the FakeNewsNet benchmark, drawing from both PolitiFact and Buz-zFeed corpora. This wo...
G. Sai, R. B. Kumar, Yalavarthi Sai Eswari· International Conference on...· 0 citations
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