Sep 29, 2009 · Abstract: This paper proposes an uncorrelated multilinear principal component analysis (UMPCA) algorithm for unsupervised subspace learning ...
This paper proposes an uncorrelated multilinear principal component analysis (UMPCA) algorithm for unsupervised subspace learning of tensorial data.
Sep 10, 2013 · This paper proposes an uncorrelated multilinear principal component analysis (UMPCA) algorithm for unsupervised subspace learning of ...
Fig. 1. Pseudocode implementation of the UMPCA algorithm for unsupervised subspace learning of tensor objects. - "Uncorrelated Multilinear Principal ...
This paper extends the classical principal component analysis (PCA) to its multilinear version by proposing a novel unsupervised dimensionality reduction ...
Abstract—This paper proposes an uncorrelated multilinear principal component analysis (UMPCA) algorithm for unsuper- vised subspace learning of tensorial ...
Uncorrelated Multilinear Principal Component Analysis (UMPCA)
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"Uncorrelated Multilinear Principal Component Analysis for Unsupervised Multilinear Subspace Learning", IEEE Transactions on Neural Networks, Vol. 20, No ...
The PCA is a classical linear method for unsupervised dimensionality ... unsupervised learning algorithms including the PCA,. MPCA and TROD, the UMPCA ...
Jan 19, 2015 · MPCA: the multilinear principal component analysis algorithm, a multilinear extension of PCA, including code, data and paper. UMPCA: the ...
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Subspace learning is an important direction in computer vision research. In this paper, a new method of tensor objects recognition based on uncorrelated ...