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Hierarchical deep semantic representation for visual categorization

文献类型：期刊论文

作者Zhang, Chunjie2,3; Li, Ruiying3; Huang, Qingming1,3; Tian, Qi4
刊名NEUROCOMPUTING
出版日期2017-09-27
卷号257页码:88-96
关键词Semantic representation Visual categorization Image representation
ISSN号0925-2312
DOI10.1016/j.neucom.2016.11.065
英文摘要Visual features are unsatisfactory to effectively describe the visual semantics. However, single layer based semantic modeling may be not able to cope with complicated semantic contents. In this paper, we propose Hierarchical Deep Semantic Representation (H-DSR), a hierarchical framework which combines semantic context modeling with visual features. First, the input image is sampled with spatially fixed grids. Deep features are then extracted for each sample in particular location. Second, using pre-learned classifiers, a detection response map is constructed for each patch. Semantic representation is then extracted from the map, which have a sense of latent semantic context. We combine the semantic and visual representations for joint representation. Third, a hierarchical deep semantic representation is built with recurrent reconstructions using three layers. The concatenated visual and semantic representations are used as the inputs of subsequent layers for semantic representation extraction. Finally, we verify the effectiveness of H-DSR for visual categorization on two publicly available datasets: Oxford Flowers 17 and UIUC-Sports. Improved performances are obtained over many baseline methods. (C) 2017 Elsevier B.V. All rights reserved.
资助项目National Natural Science Foundation of China[61303154] ; National Natural Science Foundation of China[61332016] ; National Basic Research Program of China (973 Program)[2012CB316400] ; National Basic Research Program of China (973 Program)[2015CB351802]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000404319800010
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.204/handle/2XEOYT63/7082]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Huang, Qingming
作者单位1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intell Info Proc, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
4.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
推荐引用方式
GB/T 7714		 Zhang, Chunjie,Li, Ruiying,Huang, Qingming,et al. Hierarchical deep semantic representation for visual categorization[J]. NEUROCOMPUTING,2017,257:88-96.
APA Zhang, Chunjie,Li, Ruiying,Huang, Qingming,&Tian, Qi.(2017).Hierarchical deep semantic representation for visual categorization.NEUROCOMPUTING,257,88-96.
MLA Zhang, Chunjie,et al."Hierarchical deep semantic representation for visual categorization".NEUROCOMPUTING 257(2017):88-96.

入库方式： OAI收割

来源：计算技术研究所

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