Presentation 2002/3/11
Content-Based Image Retrieval System with Computational Complexity Adjustment using Kohonen's Map
Yutaka KURAMOCHI, Kazumasa SHINJO,
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Abstract(in English) This paper proposes the content-based image retrieval system equipped with the computational complexity adjustment function using the associative memories on Kohonen's self-organizing map (SOM). This system consists of volunteer computers distributed on the communication network. Furthermore, users can specify the optimal feature extractor, because the feature extraction from an image is performed for every retrieval demand. In consideration of the feature extraction which requires computational complexity, we propose the technique of the machine-time adjustment which recovers the feature dimensions by SOM. This paper discusses the relationship between the retrieval result and retrieval time in our proposal.
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Keyword(in English) Kohonen's self-organizing map / content-based image retrieval / feature extraction / peer-to-peer network
Paper # NC2001-146
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Committee NC
Conference Date 2002/3/11(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Content-Based Image Retrieval System with Computational Complexity Adjustment using Kohonen's Map
Sub Title (in English)
Keyword(1) Kohonen's self-organizing map
Keyword(2) content-based image retrieval
Keyword(3) feature extraction
Keyword(4) peer-to-peer network
1st Author's Name Yutaka KURAMOCHI
1st Author's Affiliation ATR Adaptive Communications Research Laboratories()
2nd Author's Name Kazumasa SHINJO
2nd Author's Affiliation ATR Adaptive Communications Research Lacoratories
Date 2002/3/11
Paper # NC2001-146
Volume (vol) vol.101
Number (no) 735
Page pp.pp.-
#Pages 8
Date of Issue