Convex Multiview Semi-Supervised Classification | |
Nie, Feiping1,2; Li, Jing1,2; Li, Xuelong3 | |
刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING |
2017-12-01 | |
卷号 | 26期号:12页码:5718-5729 |
关键词 | Multiview Data Semi-supervised Classification Weight Learning |
ISSN号 | 1057-7149 |
DOI | 10.1109/TIP.2017.2746270 |
产权排序 | 3 |
文献子类 | Article |
英文摘要 | In many practical applications, there are a great number of unlabeled samples available, while labeling them is a costly and tedious process. Therefore, how to utilize unlabeled samples to assist digging out potential information about the problem is very important. In this paper, we study a multiclass semi-supervised classification task in the context of multiview data. First, an optimization method named Parametric multiview semi-supervised classification (PMSSC) is proposed, where the built classifier for each individual view is explicitly combined with a weight factor. By analyzing the weakness of it, a new adapted weight learning strategy is further formulated, and we come to the convex multiview semi-supervised classification (CMSSC) method. Comparing with the PMSSC, this method has two significant properties. First, without too much loss in performance, the newly used weight learning technique achieves eliminating a hyperparameter, and thus it becomes more compact in form and practical to use. Second, as its name implies, the CMSSC models a convex problem, which avoids the local-minimum problem. Experimental results on several multiview data sets demonstrate that the proposed methods achieve better performances than recent representative methods and the CMSSC is preferred due to its good traits. |
WOS关键词 | IMAGE CLASSIFICATION ; RECOGNITION ; INTEGRATION |
WOS研究方向 | Computer Science ; Engineering |
语种 | 英语 |
WOS记录号 | WOS:000412433000008 |
资助机构 | National Science Foundation of China(61772427) |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/29363] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Northwestern Univ, Sch Comp Sci, Xian 710072, Shaanxi, Peoples R China 2.Northwestern Univ, Ctr OPT IMagery Anal & Learning, Xian, Shaanxi, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr OPT IMagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Nie, Feiping,Li, Jing,Li, Xuelong. Convex Multiview Semi-Supervised Classification[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2017,26(12):5718-5729. |
APA | Nie, Feiping,Li, Jing,&Li, Xuelong.(2017).Convex Multiview Semi-Supervised Classification.IEEE TRANSACTIONS ON IMAGE PROCESSING,26(12),5718-5729. |
MLA | Nie, Feiping,et al."Convex Multiview Semi-Supervised Classification".IEEE TRANSACTIONS ON IMAGE PROCESSING 26.12(2017):5718-5729. |
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