Abstract

In this paper, we use deep learning to make an emotion recognition convolution neural network by customizing the EfficientNet model pretrained on the ImageNet dataset. We used the FER-2013 dataset available in the Wolfram repository. Seven classes of emotions are considered in the dataset: happy, sad, angry, surprise, disgust, fear, and neutral. We try out different methods to tackle class imbalance.