Res-SIN converts EDA signals into images and fuses them with music features to classify high/low arousal and valence, reporting 73.65% and 73.43% accuracy on PMEmo.
Pervasive and unobtrusive emotion sensing for human mental health,
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User independent Emotion Recognition with Residual Signal-Image Network
Res-SIN converts EDA signals into images and fuses them with music features to classify high/low arousal and valence, reporting 73.65% and 73.43% accuracy on PMEmo.