Writer Alternation Detection for Online Exam by Exponential Moving PCA
Writer Alternation Detection for Online Exam by Exponential Moving PCA
复制标题
指数移动 PCA 在线考试作家交替检测
DOI：
10.1109/gcce56475.2022.10014199
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Akakura Takako
中科院分区：
文献类型：
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作者：
Kawamata Taisuke;Akakura Takako
许多在线手写认证已被开发出来，以防止代理考试采取不同步的在线考试。在这里，我们提出了一种无监督的异常检测方法的基础上，从增量统计计算的主成分分析开发一个考生交替检测系统没有模板信息或预训练。评估结果表明，该系统的准确率在90%以上。
Many online handwriting authentications have been developed to prevent proxy-test taking in unsynchronized online exams. Here, we propose an unsupervised anomaly detection method based on principal component analysis calculated from incremental statistics to develop an examinee alternation detection system without template information or pre-training. The evaluation results show that the accuracy of this system is over 90%.