Title :
Classification of the Italian liras using the LVQ method
Author :
Kosaka, Toshihisa ; Omatu, Sigeru
Author_Institution :
Glory TD Himeji, Japan
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 kinds of 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 :
financial data processing; image classification; learning (artificial intelligence); neural nets; office automation; vector quantisation; Italian lira classification; LVQ method; banknotes; learning vector quantization; money; neural network; pattern classification; pattern recognition; Biological neural networks; Clustering algorithms; Focusing; Humans; Neurons; Pattern classification; Pattern matching; Pattern recognition; Pixel; Size measurement;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.861295