Use neural networks to recognize students' handwritten letters and incorrect symbols
Computer Vision and Pattern Recognition
2023-09-13 v1
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.
Keywords
Cite
@article{arxiv.2309.06221,
title = {Use neural networks to recognize students' handwritten letters and incorrect symbols},
author = {JiaJun Zhu and Zichuan Yang and Binjie Hong and Jiacheng Song and Jiwei Wang and Tianhao Chen and Shuilan Yang and Zixun Lan and Fei Ma},
journal= {arXiv preprint arXiv:2309.06221},
year = {2023}
}