Knowledge management system National Space Science Center,CAS
| Research Progress on Generative Adversarial Network with its Applications | |
| Alternative Title | 20203809211498 |
| Zhang, Zhongwei | |
| Source Publication | Proceedings of 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference, ITOEC 2020 |
| 2020 | |
| Pages | 9141685 |
| DOI | 10.1109/ITOEC49072.2020.9141685 |
| Language | 英语 |
| ISBN | 9781728143224 |
| Abstract | As a new unsupervised learning algorithm framework, generative adversarial networks(GAN) have been favored by more and more researchers, and it has become a research hotspot now. GAN is inspired by the two-person zero-sum game theory in game theory. Its unique adversarial training idea can generate high-quality samples and has more powerful feature learning and feature expression capabilities than traditional machine learning algorithms. At present, GAN has achieved remarkable success in the field of computer vision, especially in the field of sample generation. Every year, a large number of GAN-related research papers are produced, reflecting the fiery degree of research on GAN model. Aiming at the hot model of GAN, first introduce the research status of GAN; then introduce the theory and framework of GAN, which analyzes in detail why the gradient disappears and the mode collapses during the training of GAN; then discussed some typical GAN improvement models, and summarized their theoretical improvements, advantages, limitations, application scenarios and implementation costs; Finally, the application results of GAN in data generation, image super-resolution, and image style conversion are shown, and the current challenges and future research directions of GAN are discussed. © 2020 IEEE. |
| Keyword | Adversarial networks Application scenario Feature expression Future research directions Image super resolutions Implementation cost Sample generations Two-person zero-sum game |
| Conference Name | 5th IEEE Information Technology and Mechatronics Engineering Conference, ITOEC 2020 |
| Conference Date | June 12, 2020 - June 14, 2020 |
| Conference Place | Chongqing, China |
| Indexed By | EI |
| Citation statistics | |
| Document Type | 会议论文 |
| Identifier | http://ir.nssc.ac.cn/handle/122/7745 |
| Collection | 中国科学院国家空间科学中心 |
| Corresponding Author | Zhang, Zhongwei |
| Affiliation | National Space Science Center, Chinese Academy of Sciences NO. 1 Nanertiao, Zhongguancun, Haidian District, Beijing; 100190, China |
| Recommended Citation GB/T 7714 | Zhang, Zhongwei. Research Progress on Generative Adversarial Network with its Applications[C],2020:9141685. |
| Files in This Item: | There are no files associated with this item. | |||||
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