Classification of Expert-Novice Level Using Eye Tracking And Motion Data via Conditional Multimodal Variational Autoencoder

Sensor data from wearable devices have been utilized to analyze differences between experts and novices. Previous studies attempted to classify the expert-novice level from sensor data based on supervised learning methods. However, these approaches need to collect enough training data covering vario...

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Veröffentlicht in:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) S. 1360 - 1364
Hauptverfasser:	Akamatsu, Yusuke, Maeda, Keisuke, Ogawa, Takahiro, Haseyama, Miki
Format:	Tagungsbericht
Sprache:	Englisch Japanisch
Veröffentlicht:	IEEE 06.06.2021
Schlagworte:	anomaly detection expert-novice level Gaze tracking Multimodal sensors sensor data Signal processing Supervised learning Training Training data variational autoencoder Wearable computers Wearable devices
ISSN:	2379-190X
Online-Zugang:	Volltext
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