Emotion Recognition Based on the Human's Brain

Abstract

There are several different algorithms to train models in machine learning and for purpose of enhancing the accuracy of the models for emotion recognition systems by using EEG datasets, we can compare different algorithms and methods. To experience more intuitively the different impacts caused by different algorithms and methods, Emotion classification by applying Convolutional Neural Networks, Sparse Auto-encoder, Deep Neural Network, and ZTW-based epoch selection algorithm, these three models of emotion recognition will be mentioned and compared in this essay to find out a way to improve the accuracy of the emotion recognition models based on EEG datasets, which also include the process and final results of these models.