Pattern Recognition by Using Subspace Method
Research members： Dr. Seiji Hotta
Research fields： Principles of Informatics
Departments： Institute of Engineering
Keywords： pattern recognition
Web site：
Summary
Classifier design is one of the most important issues in the pattern recognition domain. Our laboratory focuses on a linear classifier called subspace method. This method maps high-dimensional samples into a low-dimensional subspace obtained by eigenvalue decomposition of an autocorrelation matrix. By using this mapping, a high-dimensional sample can be represented by a linear combination of a small number of eigenvectors. This property yields high accuracy and speed in a classification phase.
Reference articles and patents
Y. Washizawa and S. HOTTA, ''Mahalanobis Distance on Extended Grassmann Manifolds for Variational Pattern Analysis,'' IEEE Trans. on Neural Networks and Learning Systems, accepted, 2014. | doi: 10.1109/TNNLS.2014.2301178
Hiroto MINEGISHI and Seiji HOTTA, ''Vote-Based Image Classification Using Linear Manifolds,'' J. of IIEEJ, vol.40, no.1, pp.52-58, 2011.
Yosuke SHIMIZU and Seiji HOTTA, ''Detection and Retrieval of Nucleated Red Blood Cells Using Linear Subspaces,'' J. of IIEEJ, vol.40, no.1, pp.67-73, 2011.
Kzauki KONDO and Seiji HOTTA, ''Color Image Classification Using Block Matching and Learning,'' IEICE Trans. on Info. & Sys., vol.E92-D, no.7, pp.1484-1487, 2009.
Seiji HOTTA, ''Generalized Learning Local Averaging Classifier,'' J. of IIEEJ, vol.37, no.3, pp.206-213, 2008 (Paper Award from IIEEJ in 2010).
Seiji HOTTA, ''Local Subspace Classifier with Transform-Invariance for Image Classification,'' IEICE Trans. on Info. & Sys., vol.E91-D, no.6, pp.1756-1763, 2008.
Seiji HOTTA, Senya KIYASU, and Sueharu MIYAHARA, ''Arbitrary-Shaped Cluster Separation Using One-Dimensional Data Mapping and Histogram Segmentation,'' Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.9, pp.1136-1143, 2007.
Contact
University Research Administration Center(URAC),
Tokyo University of Agriculture andTechnology
urac[at]ml.tuat.ac.jp
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