Image-level classification by hierarchical structure learning with visual and semantic similarities

doi:10.1016/j.ins.2017.09.024

	Image-level classification by hierarchical structure learning with visual and semantic similarities
	Zhang, Chunjie1,4 ; Cheng, Jian2,3,4 ; Tian, Qi 5
刊名	INFORMATION SCIENCES
	2018
卷号	422 期号:422 页码:271-281
关键词	Image Classification Hierarchical Structure Learning Image-level Modeling Object Categorization
DOI	10.1016/j.ins.2017.09.024
文献子类	Article
英文摘要	Image classification methods often use class-level information without considering the distinctive character of each image. Images of the same class may have varied appearances. Besides, visually similar images may not be semantically correlated. To solve these problems, in this paper, we propose a novel image classification method by automatically learning the image-level hierarchical structure (ILHS) using both visual and semantic similarities. We try to generate new representations by exploring both visual and semantic similarities of images. Images are clustered hierarchically to explore their correlations. We then use them for image representations. The diversity of image classes within each cluster is used to re-weight visual similarities. The re-weighted similarities are aggregated to generate new image representations. We conduct image classification experiments on the Caltech-256 dataset, the PASCAL VOC 2007 dataset and the PASCAL VOC 2012 dataset. Experimental results demonstrate the effectiveness of the proposed method. (C) 2017 Elsevier Inc. All rights reserved.
WOS关键词	LOW-RANK ; SPARSE DECOMPOSITION ; REPRESENTATION ; PREDICTION ; SPACE
WOS研究方向	Computer Science
语种	英语
WOS记录号	WOS:000414887900016
资助机构	National Natural Science Foundation of China(61303154 ; Scientific Research Key Program of Beijing Municipal Commission of Education(KZ201610005012) ; ARO grant(W911NF-15-1-0290) ; NEC Laboratory of America ; NEC Laboratory of Blippar ; National Science Foundation of China (NSFC)(61429201) ; 61332016)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/15316]
专题	自动化研究所_类脑智能研究中心
作者单位	1.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
推荐引用方式 GB/T 7714	Zhang, Chunjie,Cheng, Jian,Tian, Qi. Image-level classification by hierarchical structure learning with visual and semantic similarities[J]. INFORMATION SCIENCES,2018,422(422):271-281.
APA	Zhang, Chunjie,Cheng, Jian,&Tian, Qi.(2018).Image-level classification by hierarchical structure learning with visual and semantic similarities.INFORMATION SCIENCES,422(422),271-281.
MLA	Zhang, Chunjie,et al."Image-level classification by hierarchical structure learning with visual and semantic similarities".INFORMATION SCIENCES 422.422(2018):271-281.