Presentation | 2010-01-18 Shape group representation using higher-rank SOM with affine-invariant distance measure Sho YAKUSHIJI, Takashi OHKUBO, Tetsuo FURUKAWA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This study aims to develop an observation-invariant classification algorithm of multi-class models. The task of the architecture is to classify a set of datasets, each of which is transformed differently when it is observed. Therefore it is required to remove observation-dependent component from the datasets. The higher-rank of SOM (SOM^n or 'SOM of SOMs') was employed for multi-datasets classification task, and an observation-invariant distance measured was introduced into the SOM^n algorithm. The algorithm was applied to a classification task of a set of shapes, which are transformed by affine deformation. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | self-organizing maps / distance measure / shape representaion / shape classification |
Paper # | NC2009-74 |
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Committee | NC |
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Conference Date | 2010/1/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Shape group representation using higher-rank SOM with affine-invariant distance measure |
Sub Title (in English) | |
Keyword(1) | self-organizing maps |
Keyword(2) | distance measure |
Keyword(3) | shape representaion |
Keyword(4) | shape classification |
1st Author's Name | Sho YAKUSHIJI |
1st Author's Affiliation | Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology() |
2nd Author's Name | Takashi OHKUBO |
2nd Author's Affiliation | Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology |
3rd Author's Name | Tetsuo FURUKAWA |
3rd Author's Affiliation | Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology |
Date | 2010-01-18 |
Paper # | NC2009-74 |
Volume (vol) | vol.109 |
Number (no) | 363 |
Page | pp.pp.- |
#Pages | 6 |
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