{"title":"光子学的新型深度学习技术","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":"{\"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}","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}
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.
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