@inproceedings{b927344d5ecc43e49f0a794da4311764,
title = "Use neural Networks to Recognize Students' Handwritten Letters and Incorrect Symbols",
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 = "Computer vision, Deep neural networks, images recognition, multi-classification task",
author = "Zhu, {Jia Jun} and Zichuan Yang and Binjie Hong and Jiacheng Song and Jiwei Wang and Tianhao Chen and Shuilan Yang and Zixun Lan and Fei Ma",
note = "Publisher Copyright: {\textcopyright} 2025 SPIE.; 2024 International Conference on Mechatronics and Intelligent Control, ICMIC 2024 ; Conference date: 20-09-2024 Through 22-09-2024",
year = "2025",
doi = "10.1117/12.3047738",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Kun Zhang and Pascal Lorenz",
booktitle = "International Conference on Mechatronics and Intelligent Control, ICMIC 2024",
}