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Copy Move Forgery Localization and Classification Using Pixel-Level Saliency Map U-Net With Convolutional Neural Network by vempallyrakeshimatiz is a document available to read on EtoBox.

What is Copy Move Forgery Localization and Classification Using Pixel-Level Saliency Map U-Net With Convolutional Neural Network about?

The document presents a method for copy move forgery localization and classification using a Pixel-Level Saliency Map U-Net combined with a Convolutional Neural Network (PLSMU-Net with CNN). This approach enhances localization accuracy by focusing on significant pixel-level features and effectively classifies images as tampered or authentic, achieving a high accuracy of 96.48%. The methodology utilizes the CoMoFoD dataset for evaluation, incorporating advanced techniques such as auto-correlation matching to

Author

vempallyrakeshimatiz

Language

EN