Title :
A Multi-layer Quantum Neural Networks Recognition System for Handwritten Digital Recognition
Author :
Zhu, Daqi ; Wu, Rushi
Author_Institution :
Shanghai Maritime Univ., Shanghai
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;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.70
