Adaptive image watermarking using human perception based fuzzy inference system-Reference-Cited by-同舟云学术

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Adaptive image watermarking using human perception based fuzzy inference system

Published:2018-10-27 Issue:4 Volume:35 Page:4589-4608
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Jamali Maedeh¹,Rafiei Shima¹,Soroushmehr S.M. Reza²,Karimi Nader¹,Shirani Shahram³,Najarian Kayvan²,Samavi Shadrokh¹²³

Affiliation:

1. Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran

2. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USA

3. Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference49 articles.

1. Digital watermarking applications and techniques: A brief review;Rashid;Int Journal of Computer Applications Technology and Research,2016

2. A review study on digital watermarking;Liu;in Proc IEEE International Conference on Information and Communication Technology,2005

3. A survey of digital image watermarking techniques;Potdar;in Proc IEEE International Conference on Industrial Informatics,2005

4. Robust hash for detecting and localizing image tampering;Roy;in Proc IEEE Int Conf Image Process (ICIP),2007

5. Hash-based identification of sparse image tampering;Tagliasacchi;IEEE Trans Image Process,2009

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1. Robust watermarking using diffusion of logo into auto-encoder feature maps;Multimedia Tools and Applications;2023-04-28

2. Fuzzy Logic with Superpixel-Based Block Similarity Measures for Secured Data Hiding Scheme;Lecture Notes in Networks and Systems;2022-06-28

3. Appropriate strategy selection for reliability-centered maintenance of one-shot systems using fuzzy model;Journal of Quality in Maintenance Engineering;2021-06-17

4. A Blind Watermarking Scheme Using Adaptive Neuro-Fuzzy Inference System Optimized by BP Network and LS Learning Model;Cyberspace Safety and Security;2019

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