A Deep Learning Facial Emotion Classification system: a VGGNet-19 based approach

Abstract

after studying the pretrained VGGNet 19 model, we figured out that this model contains a large number of parameters that tend likely towards overfitting, which blocks the face expression recognition performance. This indicates that there is always some room for improvement. In this manuscript, we propose a new approach based on the VGGNet-19 network, in which we use several convolution layers with small filters and a dropout strategy. In the adopted model, the addition of convolution layers is recommended in order to give more precision to image classification. The experiment results suggest that the proposed model give promising results.