Presentation 2012-11-28
Implementation of an Image Recognition System with Hierarchical Feature Learning Function
Baku OGASAWARA, Satoru YOKOTA, Hakaru TAMUKOH, Masatoshi SEKINE,
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Abstract(in English) We propose and develop "an image recognition system" having a hierarchical feature learning function. The feature learning function is combined Self-Organizing Map (SOM) with multi-resolution analysis. In this paper, we describe how to implement the image recognition system in system LSI, FPGA. The system has two sub-systems, the one is for the feature learning, and the other one is for the image recognition. These sub-systems can be integrated because of a compatibility of them. The integration saves circuit resources. In addition, we show an effectiveness of implementing feature learning and image recognition mechanism in system LSI from the learning result, the learning speed, and the logic circuit scale.
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Keyword(in English) Multi-resolution analysis / Self-Organizing Map / Image recognition / FPGA
Paper # RECONF2012-60
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Committee RECONF
Conference Date 2012/11/20(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Implementation of an Image Recognition System with Hierarchical Feature Learning Function
Sub Title (in English)
Keyword(1) Multi-resolution analysis
Keyword(2) Self-Organizing Map
Keyword(3) Image recognition
Keyword(4) FPGA
1st Author's Name Baku OGASAWARA
1st Author's Affiliation Tokyo University of Agriculture and Technology()
2nd Author's Name Satoru YOKOTA
2nd Author's Affiliation Tokyo University of Agriculture and Technology
3rd Author's Name Hakaru TAMUKOH
3rd Author's Affiliation Tokyo University of Agriculture and Technology
4th Author's Name Masatoshi SEKINE
4th Author's Affiliation Tokyo University of Agriculture and Technology
Date 2012-11-28
Paper # RECONF2012-60
Volume (vol) vol.112
Number (no) 325
Page pp.pp.-
#Pages 6
Date of Issue