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Science China Physics Mechanics and Astronomy

A quantum-search-based multi-classifier for image recognition

Lu Liu, Xingyu Wu, Lufan Zhang, Chuan Xi Wang

Published Nov 6, 2024• 3 citations
Publisher
DOI
10.1007/s11433-024-2488-5

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The facial expression recognition is an important and complicated problem of pattern recognition field.An approach to facial expression recognition based on multi-level transfer function quantum neural networks(QNN)and multi-layer classifiers is presented in order to improve the recognition rate and recognition reliability.The QNN is trained and tested by the CMU face expression image database.The experiment results show that the method achieves excellent performance in terms of recognition rates and recognition reliability,and the superiority and potential of QNN in solving pattern recognition problems are abvious.
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.