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comofod-dataset

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Copy-Move-Forgery-Detection

madhurimarawat / Copy-Move-Forgery-Detection

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This project focuses on detecting and localizing copy-move forgery in digital images using Python. Deep learning techniques are applied to identify duplicated regions within an image. The model highlights tampered areas, helping verify the image's authenticity.

python machine-learning deep-learning jupyter-notebook image-processing dataset-description comofod data-preprocessing-and-cleaning comofod-dataset
  • Updated Feb 19, 2026
  • Jupyter Notebook

sardarimohsen / Image-Forgery-Detection-Dataset

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Official repository for the Hybrid Image Forgery Detection framework. Includes implementation code and benchmarks for the CoMoFoD, MICC-2000, COVERAGE, and CASIA datasets to support large-scale image forgery localization and deep learning research.

deep-learning genetic-algorithm image-dataset image-forensics image-forgery-detection image-forgery casia-dataset comofod-dataset copy-move-forgery forgery-localization micc-2000 coverage-dataset
  • Updated Apr 30, 2026

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