Tensor Factorization and Clustering for the Feature Extraction Based on Tucker3 with Updating Core

Abstract:

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Aiming at the problems of Tucker3 to large-scale tensor when applied to feature extraction, a new factorization based on Tucker3 is proposed to extract feature from the tensors. First, the large-scale tensor is divided into multiple sub-tensors so as to conveniently compute cores of sub-tensors in parallel mode with Matlab Parallel Computing Toolbox; Then, the cores of each sub-tensor are updated for reducing deviation in calculating and the similar characteristics of sub-tensors are clustered to obtain the features. Experiment results show that this methods is able to extract features rapidly and efficiently.

Info:

Periodical:

Advanced Materials Research (Volumes 308-310)

Edited by:

Jian Gao

Pages:

2517-2522

DOI:

10.4028/www.scientific.net/AMR.308-310.2517

Citation:

H. J. Wang et al., "Tensor Factorization and Clustering for the Feature Extraction Based on Tucker3 with Updating Core", Advanced Materials Research, Vols. 308-310, pp. 2517-2522, 2011

Online since:

August 2011

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Price:

$35.00

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