Presentation | 2011-12-16 Robust Image Matching by Multiple LS-SVMs Toshitaka SHIMIZU, Hajimu KAWAKAMI, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper describes a method of designing robust classifiers of multi-class image data with multiple LS-SVMs. We first introduce an idea of the ECOC (error-correcting output code) to cause the multiple LS-SVMs to be robust. We then propose a learning method for the multiple LS-SVMs with considering the properties of the ECOC and a method of identifying multi-class image data with the multiple LS-SVMs in consideration of the properties inherent in the LS-SVM. To show effectiveness in the proposed methods, we made experiments of identifying 4-class image data in the presence of noise. The experimental results show the proposed methods possess robustness in the presence of noise. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Robust image recognition / LS-SVM / multiple classifier systems / error-correcting output code |
Paper # | PRMU2011-143 |
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Conference Information | |
Committee | PRMU |
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Conference Date | 2011/12/8(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Robust Image Matching by Multiple LS-SVMs |
Sub Title (in English) | |
Keyword(1) | Robust image recognition |
Keyword(2) | LS-SVM |
Keyword(3) | multiple classifier systems |
Keyword(4) | error-correcting output code |
1st Author's Name | Toshitaka SHIMIZU |
1st Author's Affiliation | Graduate School of Science and Technology, Ryukoku University() |
2nd Author's Name | Hajimu KAWAKAMI |
2nd Author's Affiliation | Faculty of Science and Technology, Ryukoku University |
Date | 2011-12-16 |
Paper # | PRMU2011-143 |
Volume (vol) | vol.111 |
Number (no) | 353 |
Page | pp.pp.- |
#Pages | 6 |
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