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
.
Using Deep Convolutional Neural Network for Emotion Detection on a Physiological Signals Dataset (AMIGOS)
2019
IEEE Access
Recommender systems have been based on context and content, and now the technological challenge of making personalized recommendations based on the user emotional state arises through physiological signals that are obtained from devices or sensors. This paper applies the deep learning approach using a deep convolutional neural network on a dataset of physiological signals (electrocardiogram and galvanic skin response), in this case, the AMIGOS dataset. The detection of emotions is done by
doi:10.1109/access.2018.2883213
fatcat:vz4wpuoi4rhxfbwn2bc43rcw3m