中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Spatial modeling via feature co-pooling and SG grafting

文献类型:期刊论文

作者Liu, Feng1; Huang, Yongzhen2; Wang, Liang2; Yang, Wankou1; Sun, Changyin1
刊名NEUROCOMPUTING
出版日期2014-09-02
卷号139页码:415-422
关键词Object classification Spatial modeling Feature selection
英文摘要Spatial information is an important cue for visual object analysis. Various studies in this field have been conducted. However, they are either too rigid or too fragile to efficiently utilize such information. In this paper, we propose to model the distribution of objects' local appearance patterns by using their co-occurrence at different spatial locations. In order to represent such a distribution, we propose a flexible framework called spatial feature co-pooling, with which the relations between patterns are discovered. As the final representation resulted from our framework is of high dimensionality, we propose a semi-greedy (SG) grafting algorithm to select the most discriminative features. Experimental results on the CIFAR 10, UIUC Sports and VOC 2007 datasets show that our method is effective and comparable with the state-of-art algorithms. (C) 2014 Elsevier B.V. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
关键词[WOS]IMAGE FEATURES ; CLASSIFICATION ; OBJECT
收录类别SCI
语种英语
WOS记录号WOS:000337661800038
源URL[http://ir.ia.ac.cn/handle/173211/3810]  
专题自动化研究所_智能感知与计算研究中心
作者单位1.Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China
2.Chinese Acad Sci CASIA, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Liu, Feng,Huang, Yongzhen,Wang, Liang,et al. Spatial modeling via feature co-pooling and SG grafting[J]. NEUROCOMPUTING,2014,139:415-422.
APA Liu, Feng,Huang, Yongzhen,Wang, Liang,Yang, Wankou,&Sun, Changyin.(2014).Spatial modeling via feature co-pooling and SG grafting.NEUROCOMPUTING,139,415-422.
MLA Liu, Feng,et al."Spatial modeling via feature co-pooling and SG grafting".NEUROCOMPUTING 139(2014):415-422.

入库方式: OAI收割

来源:自动化研究所

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