An Intelligent Total Score Calculation System for Test Paper

Xumin Li, Zhimin He, Huayi Xian, Haozhen Situ, Yan Zhou
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引用次数: 1

Abstract

How to correct test papers efficiently is an important problem that perplexes teachers in many colleges and universities. For the low efficiency of the total score calculation, this paper proposed an intelligent method based on image processing techniques and Convolutional Neural Network (CNN) to calculate the total score of each test paper automatically. Teachers can use the proposed system to calculate the total score of the test paper, which largely reduces teachers’ workload. The proposed model can quickly recognize and calculate the total score of test papers. The average time of the total score calculation of each test paper was 0.752 seconds in the experiment. Experimental result shows satisfying performance of the proposed method.
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智能试卷总分计算系统
如何有效地批改试卷是困扰高校教师的一个重要问题。针对总分计算效率较低的问题,本文提出了一种基于图像处理技术和卷积神经网络(CNN)的智能方法来自动计算每张试卷的总分。教师可以使用本系统计算试卷的总分,大大减少了教师的工作量。该模型可以快速识别和计算试卷总分。实验中每张试卷计算总分的平均时间为0.752秒。实验结果表明,该方法具有良好的性能。
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