| Residential College | false |
| Status | 即將出版Forthcoming |
| DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain | |
Fengpeng Li1; Kemou Li1; Haiwei Wu2; Jinyu Tian3; Jiantao Zhou1 
| |
| 2024-12 | |
| Conference Name | Neural Information Processing Systems |
| Source Publication | Neural Information Processing Systems
 |
| Conference Date | Dec 11, 2024 |
| Conference Place | Vancouver Convention Center |
| Document Type | Conference paper |
| Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
| Corresponding Author | Jiantao Zhou |
| Affiliation | 1.State Key Laboratory of Internet of Things for Smart City, University of Macau 2.Department of Computer Science, City University of Hong Kong 3.Faculty of Innovation Engineering, Macau University of Science and Technology |
| First Author Affilication | University of Macau |
| Corresponding Author Affilication | University of Macau |
| Recommended Citation GB/T 7714 | Fengpeng Li,Kemou Li,Haiwei Wu,et al. DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain[C], 2024. |
| APA | Fengpeng Li., Kemou Li., Haiwei Wu., Jinyu Tian., & Jiantao Zhou (2024). DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain. Neural Information Processing Systems. |
| Files in This Item: | There are no files associated with this item. | |||||
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