Low-Rank Tensor Completion Method for Implicitly Low-Rank Visual Data-Reference-Cited by-同舟云学术

Low-Rank Tensor Completion Method for Implicitly Low-Rank Visual Data

Author:

Ji Teng-Yu¹^ORCID,Zhao Xi-Le²^ORCID,Sun Dong-Lin³^ORCID

Affiliation:

1. School of Mathematical and Statistics, Northwestern Polytechnical University, Xi’an, Shaanxi, China

2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

3. School of Sciences, Chang’an University, Xi’an, Shaanxi, China

Funder

National Natural Science Foundation of China

Applied Basic Research Project of Sichuan Province

Key Project of Applied Basic Research in Sichuan Province

National Key Research and Development Program of China

Natural Science Foundation of Shaanxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

Reference39 articles.

2. Iterative reweighted algorithms for matrix rank minimization;mohan;J Mach Learn Res,2012

3. Adaptive low-rank kernel subspace clustering;ji,2017

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