使用基于copula的依赖源分离对正反文档进行分离

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI:10.1109/SAM48682.2020.9104250

A. Keziou, N. Mamouni, H. Fenniri

{"title":"使用基于copula的依赖源分离对正反文档进行分离","authors":"A. Keziou, N. Mamouni, H. Fenniri","doi":"10.1109/SAM48682.2020.9104250","DOIUrl":null,"url":null,"abstract":"For separating linear instantaneous mixtures of independent/dependent source components, we extend the independent/dependent blind source separation method, proposed by [1], to cover the more general case, where the dependency structure of the source components and the related parameter are both unknown. An application is given for separating scanned recto-verso documents.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Separation of recto-verso documents using copula based dependent source separation\",\"authors\":\"A. Keziou, N. Mamouni, H. Fenniri\",\"doi\":\"10.1109/SAM48682.2020.9104250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For separating linear instantaneous mixtures of independent/dependent source components, we extend the independent/dependent blind source separation method, proposed by [1], to cover the more general case, where the dependency structure of the source components and the related parameter are both unknown. An application is given for separating scanned recto-verso documents.\",\"PeriodicalId\":6753,\"journal\":{\"name\":\"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAM48682.2020.9104250\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM48682.2020.9104250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

对于分离独立/依赖源分量的线性瞬时混合物，我们扩展了[1]提出的独立/依赖盲源分离方法，以涵盖源分量的依赖结构和相关参数都未知的更一般的情况。给出了一种分离扫描的正反文档的应用程序。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Separation of recto-verso documents using copula based dependent source separation

For separating linear instantaneous mixtures of independent/dependent source components, we extend the independent/dependent blind source separation method, proposed by [1], to cover the more general case, where the dependency structure of the source components and the related parameter are both unknown. An application is given for separating scanned recto-verso documents.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)

自引率

0.00%

发文量