DocumentCode :
396680
Title :
Classification of the Italian Liras using the LVQ method
Author :
Omatu, Sigeru ; Kosaka, Toshihisa ; Teranisi, Masaru
Author_Institution :
Osaka Prefectural Univ., Sakai, Japan
Volume :
3
fYear :
2003
fDate :
20-24 July 2003
Firstpage :
2212
Abstract :
For the pattern classification problems the neuro-pattern recognition which is the pattern recognition based on the neural network approach has been paid an attention since it can classify various patterns like human beings. In this paper, we adopt the learning vector quantization(LVQ) method to classify the various money. The reasons to use the LVQ are that it can process the unsupervised classification and treat many input data with small computational burdens. We will construct the LVQ network to classify the Italian Liras. Compared with a conventional pattern matching technique, which has been adopted as a classification method, the proposed method has shown excellent classification results.
Keywords :
bank data processing; neural nets; pattern classification; unsupervised learning; vector quantisation; Italian Liras classification; LVQ method; LVQ network; bank notes; computational burdens; learning vector quantization; money classification; neural network; pattern classification; unsupervised classification; Biological neural networks; Educational institutions; Humans; Neurons; Office automation; Pattern classification; Pattern matching; Pattern recognition; Pixel; Size measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-7898-9
Type :
conf
DOI :
10.1109/IJCNN.2003.1223752
Filename :
1223752
Link To Document :
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