DocumentCode
1586154
Title
A Multi-layer Quantum Neural Networks Recognition System for Handwritten Digital Recognition
Author
Zhu, Daqi ; Wu, Rushi
Author_Institution
Shanghai Maritime Univ., Shanghai
Volume
1
fYear
2007
Firstpage
718
Lastpage
722
Abstract
In this paper, a handwritten digital recognition system based on multi-level transfer function quantum neural networks (QNN) and multi-layer classifiers is proposed. The recognition system proposed consists of two layer sub-classifiers, namely first-layer QNN coarse classifier and second-layer QNN numeral pairs classifier. Handwritten digital recognition experiments are performed by using data from MNIST database. Experiment results indicate the proposed QNN recognition system achieves excellent performance in terms of recognition rates and recognition reliability, and at the same time show the superiority and potential of QNN in solving pattern recognition problems.
Keywords
handwritten character recognition; neural nets; handwritten digital recognition; multi-layer classifiers; multi-layer quantum neural networks recognition system; Artificial neural networks; Feedforward neural networks; Handwriting recognition; Multi-layer neural network; Neural networks; Neurons; Pattern recognition; Transfer functions; Uncertainty; Weather forecasting; multi-layer classifier; multi-level transfer function; pattern recognition.; quantum neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2875-5
Type
conf
DOI
10.1109/ICNC.2007.70
Filename
4344285
Link To Document