Adversarial Learning for Invertible Steganography

Adversarial Learning for Invertible Steganography

Deep neural networks have revolutionised the research landscape of steganography. However, their potential has not been explored in invertible steganography, a special class of methods that permits the recovery of distorted objects due to steganographic perturbations to their pristine condition. In...

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Bibliographic Details
Main Author:	Ching-Chun Chang
Format:	Article
Language:	English
Published:	IEEE 2020-01-01
Series:	IEEE Access
Subjects:	Convolutional neural networks generative adversarial networks invertible steganography
Online Access:	https://ieeexplore.ieee.org/document/9245471/

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