Use neural networks to recognize students' handwritten letters and incorrect symbols

Jia Jun Zhu; Zichuan Yang; Binjie Hong; Jiacheng Song; Jiwei Wang; Tianhao Chen; Shuilan Yang; Zixun Lan; Fei Ma

doi:10.1117/12.3047738

16 January 2025 Use neural networks to recognize students' handwritten letters and incorrect symbols

Jia Jun Zhu, Zichuan Yang, Binjie Hong, Jiacheng Song, Jiwei Wang, Tianhao Chen, Shuilan Yang, Zixun Lan, Fei Ma

Author Affiliations +

Proceedings Volume 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024); 134473K (2025) https://doi.org/10.1117/12.3047738
Event: International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 2024, Wuhan, China

Abstract

Correcting students' multiple-choice answers is a repetitive and mechanical task that can be considered an image multi-classification task. Assuming possible options are 'abcd' and the correct option is one of the four, some students may write incorrect symbols or options that do not exist. In this paper, five classifications were set up - four for possible correct options and one for other incorrect writing. This approach takes into account the possibility of non-standard writing options.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jia Jun Zhu, Zichuan Yang, Binjie Hong, Jiacheng Song, Jiwei Wang, Tianhao Chen, Shuilan Yang, Zixun Lan, and Fei Ma "Use neural networks to recognize students' handwritten letters and incorrect symbols", Proc. SPIE 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 134473K (16 January 2025); https://doi.org/10.1117/12.3047738

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