深度学习:方法和应用

L. Deng, Dong Yu
{"title":"深度学习:方法和应用","authors":"L. Deng, Dong Yu","doi":"10.1561/2000000039","DOIUrl":null,"url":null,"abstract":"This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise or knowledge of the authors; (2) the application areas that have already been transformed by the successful use of deep learning technology, such as speech recognition and computer vision; and (3) the application areas that have the potential to be impacted significantly by deep learning and that have been experiencing research growth, including natural language and text processing, information retrieval, and multimodal information processing empowered by multi-task deep learning.","PeriodicalId":12340,"journal":{"name":"Found. Trends Signal Process.","volume":"27 1","pages":"197-387"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3187","resultStr":"{\"title\":\"Deep Learning: Methods and Applications\",\"authors\":\"L. Deng, Dong Yu\",\"doi\":\"10.1561/2000000039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise or knowledge of the authors; (2) the application areas that have already been transformed by the successful use of deep learning technology, such as speech recognition and computer vision; and (3) the application areas that have the potential to be impacted significantly by deep learning and that have been experiencing research growth, including natural language and text processing, information retrieval, and multimodal information processing empowered by multi-task deep learning.\",\"PeriodicalId\":12340,\"journal\":{\"name\":\"Found. Trends Signal Process.\",\"volume\":\"27 1\",\"pages\":\"197-387\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3187\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Found. Trends Signal Process.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1561/2000000039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Found. Trends Signal Process.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1561/2000000039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3187

摘要

这本专著概述了一般的深度学习方法及其在各种信号和信息处理任务中的应用。应用领域的选择有以下三个标准:(1)作者的专业知识或知识;(2)成功应用深度学习技术所改变的应用领域,例如语音识别和计算机视觉;(3)有可能受到深度学习显著影响的应用领域,以及正在经历研究增长的领域,包括自然语言和文本处理、信息检索以及多任务深度学习支持的多模式信息处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning: Methods and Applications
This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise or knowledge of the authors; (2) the application areas that have already been transformed by the successful use of deep learning technology, such as speech recognition and computer vision; and (3) the application areas that have the potential to be impacted significantly by deep learning and that have been experiencing research growth, including natural language and text processing, information retrieval, and multimodal information processing empowered by multi-task deep learning.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信