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Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution
Renwei Dian; Shutao Li; Leyuan Fang
刊名IEEE Transactions on Neural Networks and Learning Systems
2019
卷号Vol.30 No.9页码:2672-2683
关键词Spatial resolution Dictionaries Correlation Hyperspectral imaging Matrix decomposition Hyperspectral imaging image fusion low tensor-train (TT) rank (LTTR) learning superresolution
ISSN号2162-237X;2162-2388
URL标识查看原文
公开日期[db:dc_date_available]
内容类型期刊论文
URI标识http://www.corc.org.cn/handle/1471x/4613968
专题湖南大学
作者单位College of Electrical and Information Engineering, Hunan University, Changsha, China College of Electrical and Information Engineering, Hunan University, Changsha, China College of Electrical and Information Engineering, Hunan University, Changsha, China
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Renwei Dian,Shutao Li,Leyuan Fang. Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution[J]. IEEE Transactions on Neural Networks and Learning Systems,2019,Vol.30 No.9:2672-2683.
APA Renwei Dian,Shutao Li,&Leyuan Fang.(2019).Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution.IEEE Transactions on Neural Networks and Learning Systems,Vol.30 No.9,2672-2683.
MLA Renwei Dian,et al."Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution".IEEE Transactions on Neural Networks and Learning Systems Vol.30 No.9(2019):2672-2683.
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