A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Hyperdimensional Computing-based Multimodality Emotion Recognition with Physiological Signals
2019
2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
To interact naturally and achieve mutual sympathy between humans and machines, emotion recognition is one of the most important function to realize advanced human-computer interaction devices. Due to the high correlation between emotion and involuntary physiological changes, physiological signals are a prime candidate for emotion analysis. However, due to the need of a huge amount of training data for a high-quality machine learning model, computational complexity becomes a major bottleneck. To
doi:10.1109/aicas.2019.8771622
dblp:conf/aicas/ChangRBW19
fatcat:brsbrxz3prdtlenhgpemey4vnu