A Novel Semi-Supervised Dimensionality Reduction Framework

被引：0
|
作者：
Guo, Xin [1 ]
Tie, Yun [2 ]
Qi, Lin [2 ]
Guan, Ling [3 ]
机构：
[1] Zhengzhou Univ, Zhengzhou, Peoples R China
[2] Zhengzhou Univ, Sch Informat & Engn, Zhengzhou, Peoples R China
[3] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON, Canada
来源：
IEEE MULTIMEDIA | 2016年 / 23卷 / 02期
基金：
中国国家自然科学基金;
关键词：
FACE RECOGNITION;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel framework of semisupervised dimensionality reduction for multimanifold learning aims to address the issue of label insufficiency under the multimanifold assumption. Experimental results verify the advantages and effectiveness of this new framework.
引用
收藏
页码：28 / 41
页数：14
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