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Cited article:

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Copy-Move Forgery Image Detection Based on Cross-Scale Modeling and Alternating Refinement

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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

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Enhancing the Image Forgery Detection based Machine Learning Approach using Multiple Datasets

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Engineering, Technology & Applied Science Research 15 (3) 22739 (2025)
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RETRACTED ARTICLE: A survey on copy-move image forgery detection based on deep-learning techniques

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Multimedia Tools and Applications 84 (26) 30603 (2024)
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Digital Image Forgery Detection Framework based on Image Feature Enhancement and Ensemble Learning

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The Journal of Korean Institute of Information Technology 22 (6) 41 (2024)
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A Review on Image Forgery Detection Techniques Using Machine Learning

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SSRN Electronic Journal (2024)
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Enhancing Digital Image Forgery Detection Using Transfer Learning

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