A Boosting, Sparsity-Constrained Bilinear Model for Object Recognition

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	A Boosting, Sparsity-Constrained Bilinear Model for Object Recognition
	Zhang, Chunjie1 ; Liu, Jing1 ; Tian, Qi 2; Han, Yanjun ; Lu, Hanqing1 ; Ma, Songde
刊名	IEEE MULTIMEDIA
	2012-04-01
卷号	19 期号:2 页码:58-68
英文摘要	Using higher-level visual elements to represent images, the authors have developed a sparsity-constrained bilinear model (SBLM) and have combined a set of SBLMs in a boosting-like procedure to enhance performance.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Hardware & Architecture ; Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
研究领域[WOS]	Computer Science
收录类别	SCI
语种	英语
WOS记录号	WOS:000303242800007
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/3339]
专题	自动化研究所_模式识别国家重点实验室_图像与视频分析团队
作者单位	1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100864, Peoples R China 2.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX USA
推荐引用方式 GB/T 7714	Zhang, Chunjie,Liu, Jing,Tian, Qi,et al. A Boosting, Sparsity-Constrained Bilinear Model for Object Recognition[J]. IEEE MULTIMEDIA,2012,19(2):58-68.
APA	Zhang, Chunjie,Liu, Jing,Tian, Qi,Han, Yanjun,Lu, Hanqing,&Ma, Songde.(2012).A Boosting, Sparsity-Constrained Bilinear Model for Object Recognition.IEEE MULTIMEDIA,19(2),58-68.
MLA	Zhang, Chunjie,et al."A Boosting, Sparsity-Constrained Bilinear Model for Object Recognition".IEEE MULTIMEDIA 19.2(2012):58-68.