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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Forgery Detection in Digital Images by Multi-Scale Noise Estimation. [PDF]
J Imaging, 2021 Gardella M, Musé P, Morel JM, Colom M.
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DFST-UNet: Dual-Domain Fusion Swin Transformer U-Net for Image Forgery Localization. [PDF]
Entropy (Basel)Yang J, Xie A, Mai T, Chen Y.
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Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection. [PDF]
Sensors (Basel), 2021 Pu H, Huang T, Weng B, Ye F, Zhao C.
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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
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Multi-label classification for image tamper detection based on Swin-T segmentation network in the spatial domain. [PDF]
PeerJ Comput SciLi L, Zhang K, Lu J, Zhang S.
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MSCSCC-Net: multi-scale contextual spatial-channel correlation network for forgery detection and localization of JPEG-compressed image. [PDF]
Sci RepShan W, Yue J, Ding SX, Qiu J.
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Enhanced image-splicing classification: A resilient and scale-invariant approach utilizing edge-weighted local texture features. [PDF]
J Forensic SciAkram A +4 more
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A multi-model feature fusion based transfer learning with heuristic search for copy-move video forgery detection. [PDF]
Sci RepAlfraihi H +7 more
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A custom hash algorithm for hosting secure gray scale image repository in public cloud. [PDF]
Sci RepMurugesan V +2 more
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