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Identification-of-Edited-Images

Developed an artificial neural network classifier for the Detection of Human Edited Images giving above 90% accuracy and made a comparative analysis using pre-trained Image Processing models of Machine Learning (VGG16, Xception). Use of Error Level Analysis (ELA) for image pre-processing.