Factorized Tensor Dictionary Learning for Visual Tensor Data Completion

This paper aims at developing a dictionary-learning-based method for completing the visual tensor data with missing elements. Traditional dictionary learning approaches suffer from very high computational costs when processing high-dimensional tensor data. Some existing approaches for acceleration i...

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Bibliographic Details
Published in:	IEEE transactions on multimedia Vol. 23; pp. 1225 - 1238
Main Authors:	Xu, Ruotao, Xu, Yong, Quan, Yuhui
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Analytical models Constraints Convolution Convolutional codes convolutional sparse coding Dictionaries Encoding Factorization factorized dictionary learning Learning Machine learning Orthogonality Tensile stress tensor completion Tensor dictionary learning Tensors Visualization
ISSN:	1520-9210, 1941-0077
Online Access:	Get full text
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