{"title":"保护深度学习3D分类器的压缩感知方法","authors":"V. Kravets, B. Javidi, A. Stern","doi":"10.1364/3d.2022.3f3a.2","DOIUrl":null,"url":null,"abstract":"We overview methods for defending deep learning algorithms from adversarial attacks by compressive 3D sensing. With optical compressive sensing, these methods exhibit outstanding robustness to adaptive attacks.","PeriodicalId":286361,"journal":{"name":"Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Compressive Sensing Methods for Defending Deep Learning 3D Classifiers\",\"authors\":\"V. Kravets, B. Javidi, A. Stern\",\"doi\":\"10.1364/3d.2022.3f3a.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We overview methods for defending deep learning algorithms from adversarial attacks by compressive 3D sensing. With optical compressive sensing, these methods exhibit outstanding robustness to adaptive attacks.\",\"PeriodicalId\":286361,\"journal\":{\"name\":\"Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/3d.2022.3f3a.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/3d.2022.3f3a.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compressive Sensing Methods for Defending Deep Learning 3D Classifiers
We overview methods for defending deep learning algorithms from adversarial attacks by compressive 3D sensing. With optical compressive sensing, these methods exhibit outstanding robustness to adaptive attacks.
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