Research on handwriting recognition method based on machine learning

Ji Qi; HaiTao Yang; Zhuo Kong

doi:10.1117/12.2660996

2 February 2023 Research on handwriting recognition method based on machine learning

Ji Qi, HaiTao Yang, Zhuo Kong

Proceedings Volume 12462, Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022); 124622H (2023) https://doi.org/10.1117/12.2660996
Event: International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022), 2022, Xi'an, China

Abstract

Handwritten digit recognition is a process of identifying zero to nine ten digits handwritten by human hands, and its related research has always been a hot topic in the field of machine learning classification. In order to explore the accuracy of the classification recognition of handwriting bodies by K nearest neighbor classifier and MLP multilayer perceptron, this paper first introduces the relevant algorithm principle and its research progress, and then experiments on K nearest neighbor classifier and MLP multilayer perceptron and summarizes the relevant experimental data. Experiments show that in the K nearest neighbor algorithm, the classification accuracy is the highest when the number of neighbors K=3; for the MLP multilayer perceptron algorithm, the classification rate is higher when the number of neurons is larger, the number of iterations is 1000, and the learning rate is smaller.

Citation Download Citation

Ji Qi, HaiTao Yang, and Zhuo Kong "Research on handwriting recognition method based on machine learning", Proc. SPIE 12462, Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022), 124622H (2 February 2023); https://doi.org/10.1117/12.2660996

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