Name
Title | ||
|---|---|---|
A Method of Information Protection for Collaborative Deep Learning under GAN Model Attack. |
Abstract | ||
|---|---|---|
Deep learning is widely used in the medical field owing to its high accuracy in medical image classification and biological applications. However, under collaborative deep learning, there is a serious risk of information leakage based on the deep convolutional generation against the network's privacy protection method. Moreover, the risk of such information leakage is greater in the medical field.... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCBB.2019.2940583 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | DocType | Volume |
Deep learning,Generative adversarial networks,Training,Collaboration,Privacy,Biomedical imaging,Gallium nitride | Journal | 18 |
Issue | ISSN | Citations |
3 | 1545-5963 | 6 |
PageRank | References | Authors |
0.44 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaodan Yan | 1 | 12 | 1.92 |
| Baojiang Cui | 2 | 112 | 40.18 |
| Yang Xu | 3 | 83 | 8.64 |
| Peilin Shi | 4 | 6 | 0.44 |
| Ziqi Wang | 5 | 9 | 6.25 |