Classification of Italian Bills by a Competitive Neural Network
Toshihisa Kosaka, Norikazu Taketani, Sigeru Omatu · IEEJ Transactions on Electronics Information and Systems · 1999
Automatic classification of bills has become important according to the progress of office automation. This paper is concerned with the new development of bill money classification based on a competitive learning algorithm where Italian Liras are adopted for classification. The Learning Vector Quantization (LVQ) method is used as a competitive learning. Original data of Lira bills may be rotated and/or shifted. We show that the LVQ method could be used effectively to classify the Lira bills under such various conditions.