{"title":"生成对抗网络的比较研究","authors":"Akanksha Sharma, N. Jindal, A. Thakur","doi":"10.1109/ICSCCC.2018.8703267","DOIUrl":null,"url":null,"abstract":"Various new deep learning models have been invented, among which generative adversarial networks have gained exceptional prominence in last four years due to its property of image synthesis. GANs have been utilized in diverse fields ranging from conventional areas like image processing, biomedical signal processing, remote sensing, video generation to even off beat areas like sound and music generation. In this paper, we provide an overview of GANs along with its comparison with other networks, as well as different versions of Generative Adversarial Networks.","PeriodicalId":148491,"journal":{"name":"2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Comparison on Generative Adversarial Networks –A Study\",\"authors\":\"Akanksha Sharma, N. Jindal, A. Thakur\",\"doi\":\"10.1109/ICSCCC.2018.8703267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Various new deep learning models have been invented, among which generative adversarial networks have gained exceptional prominence in last four years due to its property of image synthesis. GANs have been utilized in diverse fields ranging from conventional areas like image processing, biomedical signal processing, remote sensing, video generation to even off beat areas like sound and music generation. In this paper, we provide an overview of GANs along with its comparison with other networks, as well as different versions of Generative Adversarial Networks.\",\"PeriodicalId\":148491,\"journal\":{\"name\":\"2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSCCC.2018.8703267\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCCC.2018.8703267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison on Generative Adversarial Networks –A Study
Various new deep learning models have been invented, among which generative adversarial networks have gained exceptional prominence in last four years due to its property of image synthesis. GANs have been utilized in diverse fields ranging from conventional areas like image processing, biomedical signal processing, remote sensing, video generation to even off beat areas like sound and music generation. In this paper, we provide an overview of GANs along with its comparison with other networks, as well as different versions of Generative Adversarial Networks.