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Revisiting Quantum Neural Networks for Handwritten-Digit Classification: A Reproducible Study with a Closed-Form and Ceiling Analysis

Tee Hui Teo

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.2139/ssrn.7656598

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The handwritten digital recognition is an important problem of pattern recognition field. An approach to handwritten digital recognition is presented based on multi-level transfer function quantum neural networks (QNN) and multi-layer classifiers. The QNN is trained and tested by the MNIST database. The experimental results indicate the method achieves excellent performance in terms of recognition rates and recognition reliability, and show the superiority and potential of QNN in solving pattern recognition problems.