Time Series Analysis of Physiological Data for Emotion Recognition using Deep Learning - Andreas Kamenz (2022)
A good emotion recognition is of great importance for companion systems in order to be able to respond to the user in the best possible way. In this master thesis the test setup and the laboratory study will be described. We propose serveral machine and deep learning methods to solve this problem. These methods will be implemented and compared to show that they contribute to an improved emotion recognition performance.
Keywords: Deep Learning; Machine Learning; Companion Technology; Affective Computing