Use neural networks to recognize students' handwritten letters and
  incorrect symbols
JiaJun Zhu Zichuan Yang Binjie Hong Jiacheng Song Jiwei Wang Tianhao Chen Shuilan Yang Zixun Lan Fei Ma
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.