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ID:35096801
大小:3.04 MB
页数:61页
时间:2019-03-17
《融合cca和adaboost的跨模态多媒体信息检索》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、单位代码10635学号112013321001537硕士学位论文融合CCA和Adaboost的跨模态多媒体信息检索论文作者:刘瑶指导教师:杨明副教授学科专业:计算机应用技术研究方向:机器学习与模式识别提交论文日期:2016年4月21日论文答辩日期:2016年5月29日学位授予单位:西南大学中国重庆2016年5月*A·~~~~~~~~~~m~~~fr~~~I~&~~~~~!£5JL,~~4'51fflftf!.Ac~{lt~WGHiJi&i182、E&~fu~~-~••mm~Blf*WJt!tJI~L%fl*t1-Bf1:eX;lJI.~~~i~X83、~~ft~x~~~$~m*~~~,*~x:~*~'01;~ti&jttJ¥~~iff1J[_)0~1i~x1t~~:t:a~·f~~:f:BftA:aJ~{,if6A18目录摘要.............................................................................................................................IAbstract................................4、...........................................................................................III第1章绪论....................................................................................................................11.1研究背景和意义.............................5、...................................................................11.2国内外研究现状................................................................................................21.3研究内容与创新点.....................................................................6、.......................61.4论文结构............................................................................................................6第2章相关技术概述....................................................................................................92.1文本7、特征提取方法............................................................................................92.1.1向量空间模型.........................................................................................92.1.2概率隐性语义索引..........................................8、.......................................92.1.3LDA模型..............................................................................................102.2图像特征提取方法..........................................................
2、E&~fu~~-~••mm~Blf*WJt!tJI~L%fl*t1-Bf1:eX;lJI.~~~i~X83、~~ft~x~~~$~m*~~~,*~x:~*~'01;~ti&jttJ¥~~iff1J[_)0~1i~x1t~~:t:a~·f~~:f:BftA:aJ~{,if6A18目录摘要.............................................................................................................................IAbstract................................4、...........................................................................................III第1章绪论....................................................................................................................11.1研究背景和意义.............................5、...................................................................11.2国内外研究现状................................................................................................21.3研究内容与创新点.....................................................................6、.......................61.4论文结构............................................................................................................6第2章相关技术概述....................................................................................................92.1文本7、特征提取方法............................................................................................92.1.1向量空间模型.........................................................................................92.1.2概率隐性语义索引..........................................8、.......................................92.1.3LDA模型..............................................................................................102.2图像特征提取方法..........................................................
3、~~ft~x~~~$~m*~~~,*~x:~*~'01;~ti&jttJ¥~~iff1J[_)0~1i~x1t~~:t:a~·f~~:f:BftA:aJ~{,if6A18目录摘要.............................................................................................................................IAbstract................................
4、...........................................................................................III第1章绪论....................................................................................................................11.1研究背景和意义.............................
5、...................................................................11.2国内外研究现状................................................................................................21.3研究内容与创新点.....................................................................
6、.......................61.4论文结构............................................................................................................6第2章相关技术概述....................................................................................................92.1文本
7、特征提取方法............................................................................................92.1.1向量空间模型.........................................................................................92.1.2概率隐性语义索引..........................................
8、.......................................92.1.3LDA模型..............................................................................................102.2图像特征提取方法..........................................................
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