Presentation 2014-06-26
Pattern Recognition using feature extractor of K-SVD
Hiroki SUGITA, Hiroaki SASAKI, Hayaru SHOUNO,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Feature extraction and classification are fundamental two steps in pattern recognition systems. Since feature extraction methods have been proposed based on the properties of each input data, it might be not easy to handle the method to new input data. Thus, it is important to construct a method to automatically extract features from input data. In this paper, we attempted to introduce a feature extraction method called dictionary learning. Based on dictionary learning, we build a pattern recognition system using K-SVD method which is one of methods of dictionary learning for feature extraction and verified whether the efficient how to carry out reducing features dimension.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Pattern Recognition / Dictionary Learning / K-SVD / Feature Extract
Paper # NC2014-7,IBISML2014-7
Date of Issue

Conference Information
Committee IBISML
Conference Date 2014/6/18(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Information-Based Induction Sciences and Machine Learning (IBISML)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Pattern Recognition using feature extractor of K-SVD
Sub Title (in English)
Keyword(1) Pattern Recognition
Keyword(2) Dictionary Learning
Keyword(3) K-SVD
Keyword(4) Feature Extract
1st Author's Name Hiroki SUGITA
1st Author's Affiliation The University of Electro-Communications()
2nd Author's Name Hiroaki SASAKI
2nd Author's Affiliation Tokyo Institute of Technology
3rd Author's Name Hayaru SHOUNO
3rd Author's Affiliation The University of Electro-Communications
Date 2014-06-26
Paper # NC2014-7,IBISML2014-7
Volume (vol) vol.114
Number (no) 105
Page pp.pp.-
#Pages 6
Date of Issue