Convolution Neural Networks for Blind Image Steganalysis: A Comprehensive Study | ||
| Journal of Al-Qadisiyah for Computer Science and Mathematics | ||
| Article 1, Volume 11, Issue 2, August 2019, Pages 53-64 PDF (0 K) | ||
| Authors | ||
| Hanaa Mohsin Ahmed; Halah Hasan Mahmoud | ||
| Abstract | ||
| Recently, Convolution Neural Network is widely applied in Image Classification, Object Detection, Scene labeling, Speech, Natural Language Processing and other fields. In this comprehensive study a variety of scenarios and efforts are surveyed since 2014 at yet, in order to provide a guide to further improve future researchers what CNN-based blind image steganalysis are presented its architecture, performance and limitations. Long-standing and important problem in image steganalysis difficulties mainly lie in how to give high accuracy and low payload in stego or cover images for improving performance of the network. | ||
| Keywords | ||
| deep learning; convolution neural networks; blind image steganalysis; payload | ||
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