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Real-Time Deepfake Video Detection Using Eye Movement Analysis with a Hybrid Deep Learning Approach
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Deepfake detection using deep learning methods: A systematic and comprehensive review
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The Malicious Use of AI-Based Deepfake Technology as the New Threat to Psychological Security and Political Stability
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Detecting facial manipulated images via one-class domain generalization
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Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward
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Safeguarding media integrity: A hybrid optimized deep feature fusion based deepfake detection in videos
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Deepfakes and beyond: A Survey of face manipulation and fake detection
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Fairness in face presentation attack detection
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Data-agnostic Face Image Synthesis Detection using Bayesian CNNs
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Face manipulated deepfake generation and recognition approaches: a survey
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Deep-fake video detection approaches using convolutional – recurrent neural networks
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Deepfake Detection: A Systematic Literature Review
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Image Feature Detectors for Deepfake Video Detection
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Deepfake Video Detection Using Recurrent Neural Networks
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inferredcites →https://doi.org/10.1109/icassp.2019.8683164openalex-snapshot
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inferredcites →https://doi.org/10.1109/tcds.2021.3064679openalex-snapshot
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inferredcites →https://doi.org/10.1109/tpami.2024.3362821openalex-snapshot
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inferredcites →https://doi.org/10.1109/wacv45572.2020.9093628openalex-snapshot
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inferredcites →https://doi.org/10.1109/wifs.2018.8630761openalex-snapshot
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inferredcites →https://doi.org/10.1145/3652027openalex-snapshot
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inferredcites →https://doi.org/10.1177/15248380221143772openalex-snapshot
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inferredcites →https://doi.org/10.4018/979-8-3693-1902-4.ch009openalex-snapshot
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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