{"title":"Novel deep learning techniques for photonics","authors":"M. Soljačić","doi":"10.1117/12.2593843","DOIUrl":null,"url":null,"abstract":"We present a few novel deep learning techniques for applications in \nphotonics. Of particular interest are few-shot techniques which \nminimize the amount of needed training data.","PeriodicalId":389503,"journal":{"name":"Metamaterials, Metadevices, and Metasystems 2021","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metamaterials, Metadevices, and Metasystems 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2593843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We present a few novel deep learning techniques for applications in
photonics. Of particular interest are few-shot techniques which
minimize the amount of needed training data.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
