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Multilinear Methods for Spatio-Temporal Image Recognition

Published:2017 Issue: Volume: Page:148-159
ISSN:0302-9743
Container-title:Computer Analysis of Images and Patterns
language:
Short-container-title:

Author:

Itoh Hayato,Imiya Atsushi,Sakai Tomoya

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-64689-3_12

Reference17 articles.

1. Lu, H., Plataniotis, K.N., Venetsanopoulos, A.N.: MPCA: Multilinear principal component analysis of tensor objects. IEEE Trans. Neural Networks 19(1), 18–39 (2008)

2. Lu, H., Plataniotis, K.N., Venetsanopoulos, A.N.: Uncorrelated multilinear principal component analysis for unsupervised multilinear subspace learning. IEEE Trans. Neural Networks 20(11), 1820–1836 (2009)

3. Shen, H., Huang, J.Z.: Sparse principal component analysis via regularized low rank matrix approximation. J. Multivariate Anal. 99(6), 1015–1034 (2008)

4. Vasilescu, M.A.O., Terzopoulos, D.: Multilinear (tensor) ICA and dimensionality reduction. In: Proceedings of the 7th International Conference on Independent Component Analysis and Signal Separation, pp. 818–826 (2007)

5. Panagakis, Y., Kotropoulos, C., Arce, G.R.: Non-negative multilinear principal component analysis of auditory temporal modulations for music genre classification. IEEE Trans. Audio Speech Lang. Process. 8(3), 576–588 (2010)

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