{"title":"Review and Prospect of Research on Generative Adversarial Networks","authors":"Zhao Fan, Jin Hu","doi":"10.1109/ICCSN.2019.8905263","DOIUrl":null,"url":null,"abstract":"Since it was proposed in 2014, generative adversarial networks (GAN) has been highly concerned and widely studied by industrial circles and artificial intelligence researchers. It provides a new idea for the construction of the generative model. This paper reviews the research progress of GAN and prospects its development trend. Section 2 describes the basic idea and model structure of GAN. Section 3 introduces several typical derivative models of GAN. Section 4 lists GAN's applications in many fields, such as image, vision, voice, language, and etc. Section 5 makes a forward look and thinks on the development trend of GAN, and discusses the application of GAN in the field of communication countermeasures. Finally, section 6 summarizes this paper.","PeriodicalId":330766,"journal":{"name":"2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN.2019.8905263","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Since it was proposed in 2014, generative adversarial networks (GAN) has been highly concerned and widely studied by industrial circles and artificial intelligence researchers. It provides a new idea for the construction of the generative model. This paper reviews the research progress of GAN and prospects its development trend. Section 2 describes the basic idea and model structure of GAN. Section 3 introduces several typical derivative models of GAN. Section 4 lists GAN's applications in many fields, such as image, vision, voice, language, and etc. Section 5 makes a forward look and thinks on the development trend of GAN, and discusses the application of GAN in the field of communication countermeasures. Finally, section 6 summarizes this paper.