CASIA OpenIR  > 类脑智能研究中心
Image-level classification by hierarchical structure learning with visual and semantic similarities
Zhang, Chunjie1,4; Cheng, Jian2,3,4; Tian, Qi5
2018
发表期刊INFORMATION SCIENCES
卷号422期号:422页码:271-281
文章类型Article
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.
关键词Image Classification Hierarchical Structure Learning Image-level Modeling Object Categorization
WOS标题词Science & Technology ; Technology
DOI10.1016/j.ins.2017.09.024
关键词[WOS]LOW-RANK ; SPARSE DECOMPOSITION ; REPRESENTATION ; PREDICTION ; SPACE
收录类别SCI
语种英语
项目资助者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)
WOS研究方向Computer Science
WOS类目Computer Science, Information Systems
WOS记录号WOS:000414887900016
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/15316
专题类脑智能研究中心
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.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
1-s2.0-S002002551730(3107KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
ins 录用邮件.pdf(111KB) 开放获取--浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhang, Chunjie]的文章
[Cheng, Jian]的文章
[Tian, Qi]的文章
百度学术
百度学术中相似的文章
[Zhang, Chunjie]的文章
[Cheng, Jian]的文章
[Tian, Qi]的文章
必应学术
必应学术中相似的文章
[Zhang, Chunjie]的文章
[Cheng, Jian]的文章
[Tian, Qi]的文章
相关权益政策
暂无数据
收藏/分享
文件名: 1-s2.0-S0020025517309568-main.pdf
格式: Adobe PDF
文件名: ins 录用邮件.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

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。