使用深度学习的数字图像水印:调查

IF 13.3 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Computer Science Review Pub Date : 2024-08-01 DOI:10.1016/j.cosrev.2024.100662
Khalid M. Hosny, Amal Magdi, Osama ElKomy, Hanaa M. Hamza
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引用次数: 0

摘要

近来,确保数字图像所有权的问题备受关注。互联网使用的不断扩大引发了一些问题,包括数据盗版和数据篡改。图像水印是保护图像版权的一种典型方法。数字图像的鲁棒水印是在封面图像上嵌入水印并在不同攻击下正确提取水印的过程。嵌入的水印可以是可见的,也可以是不可见的。深度学习利用神经网络提取图像特征,在特征提取方面非常有效。利用深度学习提取特征的水印技术因其卓越的能力而备受关注。本文概述了数字图像水印和深度学习。本文将讨论深度学习环境下数字图像水印的几篇研究文章。
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Digital image watermarking using deep learning: A survey

Lately, a lot of attention has been paid to securing the ownership rights of digital images. The expanding usage of the Internet causes several problems, including data piracy and data tampering. Image watermarking is a typical method of protecting an image's copyright. Robust watermarking for digital images is a process of embedding watermarks on the cover image and extracting them correctly under different attacks. The embedded watermark might be either visible or invisible. Deep learning extracts image features using neural networks, which are highly effective in feature extraction. Watermarking techniques that utilize deep learning have gained a lot of interest due to their remarkable ability to extract features. This article offers an overview of digital image watermarking and deep learning. This article will discuss several research articles on digital image watermarking in deep-learning environments.

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来源期刊
Computer Science Review
Computer Science Review Computer Science-General Computer Science
CiteScore
32.70
自引率
0.00%
发文量
26
审稿时长
51 days
期刊介绍: Computer Science Review, a publication dedicated to research surveys and expository overviews of open problems in computer science, targets a broad audience within the field seeking comprehensive insights into the latest developments. The journal welcomes articles from various fields as long as their content impacts the advancement of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.
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