Calibrating the classifier: siamese neural network architecture for end-to-end arousal recognition from ECG

Calibrating the classifier: siamese neural network architecture for end-to-end arousal recognition from ECG

Affective analysis of physiological signals enables emotion recognition in mobile wearable devices. In this paper, we present a deep learning framework for arousal recognition from ECG (electrocardio- gram) signals. Specifically, we design an end-to-end convolutional and recurrent neural network arc...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy:	Patane, A, Kwiatkowska, M
Format:	Conference item
Wydane:	Springer Verlag 2019

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