Presentation | 2014-06-26 Pattern Recognition using feature extractor of K-SVD Hiroki SUGITA, Hiroaki SASAKI, Hayaru SHOUNO, |
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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 |
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Committee | IBISML |
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Conference Date | 2014/6/18(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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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 |
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