Learning Feature Hierarchies: A Layer-Wise Tag-Embedded Approach
Yuan, Zhaoquan1; Xu, Changsheng1; Sang, Jitao1; Yan, Shuicheng2; Hossain, M. Shamim3
2015-06-01
发表期刊IEEE TRANSACTIONS ON MULTIMEDIA
卷号17期号:6页码:816-827
文章类型Article
摘要Feature representation learning is an important and fundamental task in multimedia and pattern recognition research. In this paper, we propose a novel framework to explore the hierarchical structure inside the images from the perspective of feature representation learning, which is applied to hierarchical image annotation. Different from the current trend in multimedia analysis of using pre-defined features or focusing on the end-task "flat" representation, we propose a novel layer-wise tag-embedded deep learning (LTDL) model to learn hierarchical features which correspond to hierarchical semantic structures in the tag hierarchy. Unlike most existing deep learning models, LTDL utilizes both the visual content of the image and the hierarchical information of associated social tags. In the training stage, the two kinds of information are fused in a bottom-up way. Supervised training and multi-modal fusion alternate in a layer-wise way to learn feature hierarchies. To validate the effectiveness of LTDL, we conduct extensive experiments for hierarchical image annotation on a large-scale public dataset. Experimental results show that the proposed LTDL can learn representative features with improved performances.
关键词Auto-encoder Deep Learning Hierarchical Feature Learning Social Tags
WOS标题词Science & Technology ; Technology
关键词[WOS]CLASSIFICATION ; MULTIMEDIA ; MODELS ; REPRESENTATION ; RECOGNITION ; DICTIONARY ; MULTIPLE ; DATABASE
收录类别SCI
语种英语
WOS研究方向Computer Science ; Telecommunications
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS记录号WOS:000354527500005
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/8079
专题模式识别国家重点实验室_多媒体计算与图形学
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 119077, Singapore
3.King Saud Univ, SWE Dept, Coll Comp & Informat Sci, Riyadh 11543, Saudi Arabia
推荐引用方式
GB/T 7714
Yuan, Zhaoquan,Xu, Changsheng,Sang, Jitao,et al. Learning Feature Hierarchies: A Layer-Wise Tag-Embedded Approach[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2015,17(6):816-827.
APA Yuan, Zhaoquan,Xu, Changsheng,Sang, Jitao,Yan, Shuicheng,&Hossain, M. Shamim.(2015).Learning Feature Hierarchies: A Layer-Wise Tag-Embedded Approach.IEEE TRANSACTIONS ON MULTIMEDIA,17(6),816-827.
MLA Yuan, Zhaoquan,et al."Learning Feature Hierarchies: A Layer-Wise Tag-Embedded Approach".IEEE TRANSACTIONS ON MULTIMEDIA 17.6(2015):816-827.
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
12A Layer-Wise Tag-E(1750KB)期刊论文作者接受稿开放获取CC BY-NC-SA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
[Yuan, Zhaoquan]的文章
[Xu, Changsheng]的文章
[Sang, Jitao]的文章
百度学术
百度学术中相似的文章
[Yuan, Zhaoquan]的文章
[Xu, Changsheng]的文章
[Sang, Jitao]的文章
必应学术
必应学术中相似的文章
[Yuan, Zhaoquan]的文章
[Xu, Changsheng]的文章
[Sang, Jitao]的文章
相关权益政策
暂无数据
收藏/分享
文件名: 12A Layer-Wise Tag-Embedded Approach.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。