Deep learning and multi-statistical features: an intra-frame forgery detection video method. [PDF]
Front Artif IntellUliyan D +4 more
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The progressive image copy-move forgery detection based on attention mechanism
四川大学学报. 自然科学版To address the problem of information loss in the feature extraction stage of deep-learning-based methods for image copy-move forgery detection， a progressive image copy-move forgery detection model based on the attention mechanism is proposed.This model
LIU Liang, HE Wen-Jing, ZHANG Lei
doaj
DeepForgeryNet: a hybrid CNN-LSTM and transfer learning framework for robust image forgery and deepfake detection. [PDF]
Front Artif IntellSardhara A +3 more
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Stacked multi-fusion CNN: an adaptive attention model for privacy preserving deepfake forensics. [PDF]
Sci RepRout J +5 more
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Hybrid framework for image forgery detection and robustness against adversarial attacks using vision transformer and SVM. [PDF]
Sci RepAbdelmaksoud M +3 more
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Interpol review of forensic image and video analysis, 2022-2025. [PDF]
Forensic Sci Int SynergGeradts Z, van Lierop S, Kombrink M.
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IoT-Oriented Security for Small Sensor Systems Using DnCNN Denoising and Multimodal Feature Fusion for Image Forgery Detection. [PDF]
Sensors (Basel)Nasir N, Waseem SS, Bilal M, Hassan SR.
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Multi-resolution transfer learning for tampered image classification using SE-enhanced fused-MBConv and optimized CNN heads. [PDF]
Sci RepKorsipati JR +4 more
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SFTA-Net: a self-supervised approach to detect copy-move and splicing forgery to leverage triplet loss, auxiliary loss, and spatial attention. [PDF]
PeerJ Comput SciAlabrah A.
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Image tampering detection using dynamic histogram equalization based LIOP features and novel scaled K-means + + clustering. [PDF]
Sci RepMehmood Z +5 more
europepmc +1 more source