Kernel-Based Multiview Joint Sparse Coding for Image Annotation

It remains a challenging task for automatic image annotation problem due to the semantic gap between visual features and semantic concepts. To reduce the gap, this paper puts forward a kernel-based multiview joint sparse coding (KMVJSC) framework for image annotation. In KMVJSC, different visual fea...

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Vydané v:	Mathematical problems in engineering Ročník 2017; číslo 2017; s. 1 - 11
Hlavní autori:	Zang, Miao, Zhang, Yongmei, Xu, Huimin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cairo, Egypt Hindawi Publishing Corporation 01.01.2017 Hindawi John Wiley & Sons, Inc
Predmet:	Algorithms Annotations Classification Coding Colleges & universities Greedy algorithms Hardware reviews Image annotation Image coding Image retrieval Kernels Labels Learning Mathematical problems Methods Optimization Parameter estimation Semantics Singular value decomposition Sparsity Visual discrimination Visual tasks
ISSN:	1024-123X, 1563-5147
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