Presentation | 2008-12-18 Automatic Category Classification of Self-Organizing Maps Using Adaptive Learning Masahiro TSUKADA, Hirokazu MADOKORO, Kazuhito SATO, |
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Abstract(in English) | This paper presents a method for automatic category classification using a network system that combine additional learning function of ART-2 (Adaptive Resonance Theory) networks, self-representation characteristic of CPN (Counter Propagation Networks), and local feature descriptors by SIFT (Scale-Invariant Feature Transform). In our method, we are possible unsupervised automatic category classification. Our proposed method consists of three important elements: 1) automatic category labeling by ART networks; 2) visiblize spatial relations between categories by CPN; and 3)produce our original histograms basing on vector quantizing SIFT descriptors. Experiment results that used Caltech-256 Object Category Dataset show that our method can successfully build categories from an unsupervised analysis of images. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | ART-2 / CPN / SOM / SIFT / Automatic category classification |
Paper # | PRMU2008-148 |
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Committee | PRMU |
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Conference Date | 2008/12/11(1days) |
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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) | Automatic Category Classification of Self-Organizing Maps Using Adaptive Learning |
Sub Title (in English) | |
Keyword(1) | ART-2 |
Keyword(2) | CPN |
Keyword(3) | SOM |
Keyword(4) | SIFT |
Keyword(5) | Automatic category classification |
1st Author's Name | Masahiro TSUKADA |
1st Author's Affiliation | Faculty of Systems Science and Technology, Akita Prefectural University() |
2nd Author's Name | Hirokazu MADOKORO |
2nd Author's Affiliation | Faculty of Systems Science and Technology, Akita Prefectural University |
3rd Author's Name | Kazuhito SATO |
3rd Author's Affiliation | Faculty of Systems Science and Technology, Akita Prefectural University |
Date | 2008-12-18 |
Paper # | PRMU2008-148 |
Volume (vol) | vol.108 |
Number (no) | 363 |
Page | pp.pp.- |
#Pages | 6 |
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