1998 Fiscal Year Final Research Report Summary
Bill Money Classification for Intelligent OA Systems Using Evolutional Neural Networks
| Project/Area Number |
09555131
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
計測・制御工学
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| Research Institution | Osaka Prefecture University |
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Principal Investigator |
OMATU Sigeru Osaka Prefecture University, Department of Computer and Systems Sciences, Professor, 工学部, 教授 (30035662)
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| Co-Investigator(Kenkyū-buntansha) |
TAKEDA Fumiaki Glory LTD,Development Center of New Technology, Chief Scientist, 研究開発センター, 研究主幹
YOSHIOKA Michifumi Osaka Prefecture University, Department of Computer and Systems Sciences, Profes, 工学部, 講師 (70285302)
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| Project Period (FY) |
1997 – 1998
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| Keywords | Neural networks / Neuro-classification / Evolutional computation / Bill money classification / Digital signal processing / Neuro-board |
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| Research Abstract |
In this project, we have proposed a new approach to realize the intelligent pattern classification of bill money to enforce the office automation based on neural networks with evolution mechanism. The present project is to synthesize an intelligent pattern classifier system. To complete the project study, we have adopted the following approach to synthesize these intelligent control systems :
(1) Learning Ability of the Neural network
We have formulated the learning ability of neural networks by using information measure of the communication channel.
(2) Emergence of Evolution Mechanism by Genetic Algorithms
To improve the learning ability of neural networks considered (1), we have introduced the genetic algorithms and find the global minimum of the learning curves.
(3) Construction of Image Understanding by Neural Networks
To realize the intelligence we have used not only numerical data but also image information processing as a multi-media data processing.
(4) Hardware Implementation of Neuro-Classifier
In order to speed up the classification and make the cost lower, we have implemented the neuro- hardware for bill money classification.
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