Nov 13, 2022 · In this paper, for the first time, we formulate detecting disengagement in virtual learning as an anomaly detection problem.

Jun 12, 2023 · In this paper, for the first time, we formulate detecting disengagement in virtual learning as an anomaly detection problem.

The result of the experiments shows the superiority of the proposed approach for disengagement detection as an anomaly compared to binary classifiers for ...

... detecting dis- engagement in virtual learning as an anomaly detection problem. We design various autoencoders, including temporal convolutional network.

Detecting disengagement in virtual learning as an anomaly using temporal convolutional network autoencoder. https://doi.org/10.1007/s11760-023-02578-z.

To handle this situation, in this paper, for the first time, we formulate detecting disengagement in virtual learning as an anomaly detection problem. We ...

Student engagement is an important factor in meeting the goals of virtuallearning programs. Automatic measurement of student engagement provides ...

Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder. Shehroz S. Khan, Ali Abedi. 12 Nov 2022. Previous; 1 ...

Detecting disengagement in virtual learning as an anomaly using temporal convolutional network autoencoder. 自编码 脱离理论 二元分类 计算机科学 异常检测 人工 ...

Anomaly detection frameworks using autoencoders and their variants can be used for fall detection due to the data imbalance that arises from the rarity and ...