Preprocessing Strategy to Improve the Performance of Convolutional Neural Networks Applied to Steganalysis in the Spatial Domain
Mario Alejandro Bravo-Ortiz,
Esteban Mercado-Ruiz,
Juan Pablo Villa-Pulgarin
et al.
Abstract:Recent research has shown that deep learning techniques outperform traditional steganography and steganalysis methods. As a result, researchers have proposed increasingly complex and more extensive convolutional Neural Networks (CNNs) to detect Steganographic images to achieve a 1%-2% improvement over the state-of-the-art. In this paper, we propose a data preprocessing and distribution strategy that enhances accuracy and convergence during training. Our method involves bifurcating Spatial Rich Model (SRM) and … Show more
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