Presentation | 2001/3/16 Fuzzy Clustering Based on Similarity Matrix Kiichi URAHAMA, Kohei INOUE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | A method is presented for fuzzy clustering of data based on similarity matrix. Fuzzy clustering is formulated by an optimization problem and its iterative solution procedure is derived. Extraction of each cluster is reduced to an eigenvalue problem. Clusters are extracted from a major one to minor ones and the number of clusters is estimated by the profile of total extraction degree of data. Approximate forms of cluster obtained by this sequential extraction process can be refined by cyclic iteration of cluster extraction to convergence. Performance of the method is examined by simple data and it is applied to segmentation of videos and still images. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | fuzzy clustering / similarity matrix / sequential iteration / eigen-decomposition |
Paper # | PRMU2000-236 |
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Conference Information | |
Committee | PRMU |
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Conference Date | 2001/3/16(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) | Fuzzy Clustering Based on Similarity Matrix |
Sub Title (in English) | |
Keyword(1) | fuzzy clustering |
Keyword(2) | similarity matrix |
Keyword(3) | sequential iteration |
Keyword(4) | eigen-decomposition |
1st Author's Name | Kiichi URAHAMA |
1st Author's Affiliation | Faculty of Visual Communication Design, Kyushu Institute of Design() |
2nd Author's Name | Kohei INOUE |
2nd Author's Affiliation | Faculty of Visual Communication Design, Kyushu Institute of Design |
Date | 2001/3/16 |
Paper # | PRMU2000-236 |
Volume (vol) | vol.100 |
Number (no) | 702 |
Page | pp.pp.- |
#Pages | 6 |
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