Convolution neural networks for blind image steganalysis : a comprehensive study

Other Title(s)

الشبكات العصبية التلافيفية لتحليل الإخفاء الأعمى في الصورة : دراسة شاملة

Joint Authors

Ahmad, Hana Muhsin
Mahmud, Halah Hasan

Source

al-Qadisiyah Journal for Computer Science and Mathematics

Issue

Vol. 11, Issue 2 (31 Dec. 2019), pp.53-64, 12 p.

Publisher

University of al-Qadisiyah College of computer Science and Information Technology

Publication Date

2019-12-31

Country of Publication

Iraq

No. of Pages

12

Main Topic

Information Technology and Computer Science

Abstract EN

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.

American Psychological Association (APA)

Ahmad, Hana Muhsin& Mahmud, Halah Hasan. 2019. Convolution neural networks for blind image steganalysis : a comprehensive study. al-Qadisiyah Journal for Computer Science and Mathematics،Vol. 11, no. 2, pp.53-64.
https://search.emarefa.net/detail/BIM-883449

Modern Language Association (MLA)

Ahmad, Hana Muhsin& Mahmud, Halah Hasan. Convolution neural networks for blind image steganalysis : a comprehensive study. al-Qadisiyah Journal for Computer Science and Mathematics Vol. 11, no. 2 (2019), pp.53-64.
https://search.emarefa.net/detail/BIM-883449

American Medical Association (AMA)

Ahmad, Hana Muhsin& Mahmud, Halah Hasan. Convolution neural networks for blind image steganalysis : a comprehensive study. al-Qadisiyah Journal for Computer Science and Mathematics. 2019. Vol. 11, no. 2, pp.53-64.
https://search.emarefa.net/detail/BIM-883449

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 63

Record ID

BIM-883449