作者
Kunfeng Wang, Chao Gou, Yanjie Duan, Yilun Lin, Xinhu Zheng, Fei-Yue Wang
发表日期
2017/9/15
来源
IEEE/CAA Journal of Automatica Sinica
卷号
4
期号
4
页码范围
588-598
出版商
IEEE
简介
Recently, generative adversarial networks U+0028 GANs U+0029 have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adversarial learning idea. The goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that distribution. Since their initiation, GANs have been widely studied due to their enormous prospect for applications, including image and vision computing, speech and language processing, etc. In this review paper, we summarize the state of the art of GANs and look into the future. Firstly, we survey GANs U+02BC proposal background, theoretic and implementation models, and application fields. Then, we discuss GANs U+02BC advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs …
学术搜索中的文章
K Wang, C Gou, Y Duan, Y Lin, X Zheng, FY Wang - IEEE/CAA Journal of Automatica Sinica, 2017