CCCIH: Content-consistency Coverless Information Hiding Method Based on Generative Models-Reference-Cited by-同舟云学术

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CCCIH: Content-consistency Coverless Information Hiding Method Based on Generative Models

Published:2021-07-10 Issue:6 Volume:53 Page:4037-4046
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Li Qi,Wang Xingyuan,Wang Xiaoyu,Shi Yunqing

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jilin Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

https://link.springer.com/content/pdf/10.1007/s11063-021-10582-y.pdf

Reference22 articles.

1. Wang XY, Wang XY, Ma B, Li Q, Shi YQ (2021) High precision error prediction algorithm based on ridge regression predictor for reversible data hiding. IEEE Signal Process Lett. https://doi.org/10.1109/LSP.2021.3080181

2. Wu KC, Wang CM (2014) Steganography using reversible texture synthesis. IEEE Trans Image Process 24(1):130–139

3. Li Q, Wang XY, Wang XY, Ma B, Wang CP, Shi YQ (2020) An encrypted coverless information hiding method based on generative models. Inf Sci 553(3)

4. Hu YC (2006) High-capacity image hiding scheme based on vector quantization. Pattern Recognit 39(9):1715–1724

5. Wang XY, Gao S (2020) Image encryption algorithm for synchronously updating Boolean networks based on matrix semi-tensor product theory. Inf Sci 507:16–36

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