中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Beyond global fusion: A group-aware fusion approach for multi-view image clustering

文献类型：期刊论文

作者Wang, Shuhui3; Huang, Jun2,5; Zhang, Weigang1; Huang, Qingming3,4,5; Xue, Zhe5,6; Li, Guorong4,5
刊名INFORMATION SCIENCES
出版日期2019-08-01
卷号493页码:176-191
关键词Multi-view learning Local fusion strategy Group-aware fusion Image clustering
ISSN号0020-0255
DOI10.1016/j.ins.2019.04.034
英文摘要Images can be represented by multiple views and each view describes a specific visual appearance. Compared with single view learning method, multi-view methods can integrate information of different views to generate better clustering performance. Most of the existing multi-view methods assume that the importance of each view is the same to all the images. However, since visual appearance of images are different, the description abilities of different features vary with images. To solve this problem, a group-aware multi-view fusion approach is proposed in this paper. Specifically, images are partitioned into groups according to their visual appearance, and different fusion weights are assigned to different groups. We develop two paradigms under our group-aware fusion framework: pair-wise fusion and center-wise fusion. The former focuses on generating more accurate fusion results, while the latter achieves lower computational complexity. We design an optimization objective function which combines consensus and discrimination criterion to select more reliable and discriminative views for multi-view fusion. The clustering results and the fusion weights are learned by an iterative optimization algorithm. Experiments on four real-world image datasets indicate that our approach achieves promising image clustering performance over the existing methods. (C) 2019 Elsevier Inc. All rights reserved.
资助项目National Natural Science Foundation of China[61620106009] ; National Natural Science Foundation of China[61802028] ; National Natural Science Foundation of China[61836002] ; National Natural Science Foundation of China[61772494] ; National Natural Science Foundation of China[U1636214] ; National Natural Science Foundation of China[61472389] ; National Natural Science Foundation of China[61532006] ; National Natural Science Foundation of China[61877006] ; National Natural Science Foundation of China[61772083] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-SYS013] ; Youth Innovation Promotion Association CAS ; Fundamental Research Funds for the Central University[2018RC44] ; Chinese Academy of Sciences ; Director Foundation of Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia[ITSM20180102]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000470052500011
出版者ELSEVIER SCIENCE INC
源URL[http://119.78.100.204/handle/2XEOYT63/4203]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Li, Guorong
作者单位1.Harbin Inst Technol, Sch Comp Sci & Technol, Weihai 264209, Peoples R China
2.Anhui Univ Technol, Sch Comp Sci & Technol, Maanshan, Peoples R China
3.Chinese Acad Sci, Inst Comput Tech, Key Lab Intell Info Proc, Beijing 100080, Peoples R China
4.Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing, Peoples R China
5.Univ Chinese Acad Sci CAS, Sch Comp Sci & Technol, Beijing 100190, Peoples R China
6.Beijing Univ Posts & Telecommun, Sch Comp Sci, Beijing Key Lab Intelligent Telecommun Software &, Beijing 100876, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Shuhui,Huang, Jun,Zhang, Weigang,et al. Beyond global fusion: A group-aware fusion approach for multi-view image clustering[J]. INFORMATION SCIENCES,2019,493:176-191.
APA Wang, Shuhui,Huang, Jun,Zhang, Weigang,Huang, Qingming,Xue, Zhe,&Li, Guorong.(2019).Beyond global fusion: A group-aware fusion approach for multi-view image clustering.INFORMATION SCIENCES,493,176-191.
MLA Wang, Shuhui,et al."Beyond global fusion: A group-aware fusion approach for multi-view image clustering".INFORMATION SCIENCES 493(2019):176-191.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。