Generative Adversarial Networks: Introduction and Outlook

doi:10.1109/JAS.2017.7510583

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Generative Adversarial Networks: Introduction and Outlook
	Kunfeng Wang1,2 ; Chao Gou1,3 ; Yanjie Duan1,3 ; Yilun Lin1,3 ; Xinhu Zheng 4; Fei-Yue Wang1,5
发表期刊	IEEE/CAA Journal of Automatica Sinica
	2017-10
卷号	4 期号:4 页码:588-598
摘要	Recently, generative adversarial networks (GANs) 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’ proposal background, theoretic and implementation models, and application fields. Then, we discuss GANs’ advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs and parallel intelligence, with the conclusion that GANs have a great potential in parallel systems research in terms of virtual-real interaction and integration. Clearly, GANs can provide substantial algorithmic support for parallel intelligence.
关键词	Acp Approach Adversarial Learning Generative Adversarial Networks (Gans) Generative Models Parallel Intelligence Zero-sum Game
DOI	10.1109/JAS.2017.7510583
收录类别	EI
语种	英语
引用统计	被引频次：298[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/20215
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
作者单位	1.Institute of Automation, Chinese Academy of Sciences 2.Qingdao Academy of Intelligent Industries 3.University of Chinese Academy of Sciences 4.University of Minnesota 5.National University of Defense Technology
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Kunfeng Wang,Chao Gou,Yanjie Duan,et al. Generative Adversarial Networks: Introduction and Outlook[J]. IEEE/CAA Journal of Automatica Sinica,2017,4(4):588-598.
APA	Kunfeng Wang,Chao Gou,Yanjie Duan,Yilun Lin,Xinhu Zheng,&Fei-Yue Wang.(2017).Generative Adversarial Networks: Introduction and Outlook.IEEE/CAA Journal of Automatica Sinica,4(4),588-598.
MLA	Kunfeng Wang,et al."Generative Adversarial Networks: Introduction and Outlook".IEEE/CAA Journal of Automatica Sinica 4.4(2017):588-598.

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