A Benchmark for Homework Tidiness Assessment

2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2019-12-01 DOI:10.1109/ISPACS48206.2019.8986287

Hanxiao Wu, Zhenyu Zhang, Zhichao Zheng, Fei Shen, Weiwei Zhang, Jianqing Zhu, Huanqiang Zeng

引用次数: 0

Abstract

The homework tidiness assessment aims to auto evaluate the writing tidiness of homework, playing an important role in daily teaching. However, there is still no comprehensive basis for homework tidiness assessment. For this, a benchmark for homework tidiness assessment (HTA) is proposed. Firstly, a database named HTA 1.0 containing 1000 homework images is collected. Each image is manually annotated by multiple volunteers. Secondly, a comprehensive evaluation protocol is designed, using mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and accuracy (Acc) as performance indicators. Finally, three deep learning models (i.e., LeNet, AlexNet and VGGNet) are applied as baseline methods and the results are reported and analyzed.

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家庭作业整洁度评估基准

作业整洁性评价旨在对作业的写作整洁性进行自动评价，在日常教学中发挥着重要作用。然而，对家庭作业整洁性的评价仍然缺乏全面的依据。为此，提出了作业整洁性评价的基准。首先，收集一个名为HTA 1.0的数据库，其中包含1000张作业图片。每张图片都由多名志愿者手工标注。其次，设计了以平均绝对误差(MAE)、均方根误差(RMSE)、平均绝对百分比误差(MAPE)和准确率(Acc)为性能指标的综合评价方案。最后，将三个深度学习模型(即LeNet、AlexNet和VGGNet)作为基准方法，并对结果进行了报告和分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

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