Assessing the Efficacy of Invisible Watermarks in AI-Generated Medical Images
Author:
Affiliation:
1. Imperial College London,Department of Bioengineering,London,UK
2. University of Leicester,Computing and Mathematic Sciences,Leicester,UK
3. Imperial College London,National Heart and Lung Institute,London,UK
Funder
Royal Society
Boehringer Ingelheim
NIHR Imperial Biomedical Research Centre
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635746.pdf?arnumber=10635746
Reference12 articles.
1. SMOTE: Synthetic Minority Over-sampling Technique
2. Synthetic Medical Images for Robust, Privacy-Preserving Training of Artificial Intelligence
3. Emerging concern of scientific fraud: Deep learning and image manipulation;Qi,2020
4. Will Large-scale Generative Models Corrupt Future Datasets?
5. Reversible Data Hiding Using Non-local Means Prediction
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