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Fake Image Detector

Image Tampering Detection using ELA and CNN


Members

  1. Agus Gunawan
  2. Holy Lovenia
  3. Adrian Hartanto Pramudita

Indonesian paper/documentation

Get it here!

Project objective

Combine the implementation of error-level analysis (ELA) and deep learning to detect whether an image has undergone fabrication or/and editing process or not, e.g. splicing.

Methods

  1. Error-level analysis
  2. Convolutional neural networks (CNN)

Architecture

full-architecture

Result

  • Convergence: Epoch 9
  • Best accuracy: 91.83% (epoch 9)

Dataset

Please refer to issue #1.

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Image Tampering Detection using ELA and CNN

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