Intelligent grading system based on deep learning

Author:

Xiao Meng1,Yi Haibo2ORCID

Affiliation:

1. School of Management, Shenzhen Polytechnic, Shenzhen, China

2. School of Artificial Intelligence, Shenzhen Polytechnic, Shenzhen, China

Abstract

According to the survey, off-line examination is still the main examination method in universities, primary and secondary schools. The grading processing of off-line examination is time-consuming. Besides, since the off-line grading is subjective, it is error-prone. In order to address the challenges in off-line examinations of universities, primary and secondary schools, it is very urgent to improve the efficiency of off-line grading. In order to realize intelligent grading for off-line examinations, we exploit deep learning techniques to off-line grading. First, we propose an image processing method for English letters. Second, we propose a image recognition method based on deep learning for English letters. Third, we propose a lightweight framework for grading. Based on the above designs, we design an intelligent grading system based on deep learning. We implement the system and the result shows that the intelligent grading system can batch grading efficiently. Besides, compared with related designs, the proposed system is more flexible and intelligent.

Funder

Natural Science Foundation of Guangdong Province, China

Foundation for Distinguished Young Talents in Higher Education of Guangdong, China

Publisher

SAGE Publications

Subject

Electrical and Electronic Engineering,Education

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on English Reading Motivation and Its Influencing Factors in Social Network Environment;Applied Mathematics and Nonlinear Sciences;2024-01-01

2. Research and Implementation of Intelligent Financial Audit System Based on Deep Learning;2022 International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS);2022-07

3. Student Authentication and Proctoring System Using AI and the IoT;2022 2nd International Conference on Computing and Machine Intelligence (ICMI);2022-04-15

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