Facial Image Expression Recognition and Prediction System

Abstract Facial expression recognition system is an advanced technology that allows machines to recognize human emotions based on their facial expressions. We will use a dataset of human picture facial images in this research, which has more than 35500 facial photographs and represents seven different types of facial expression. To create our prediction model, we will use three different architecture models to create a system for predicting face expressions in people. We will analyze our data and make every effort to remove as much noise as we can before feeding that information to our model. We use the confusion matrix to assess the model's performance after it has been implemented effectively. To demonstrate the effectiveness of our model architecture, we will generate bar graphs and scatter plots for each model to display model loss and accuracy. The output of this model are visualize with actual class and predictive class and the result have graphical representation for each and every output facial Images which makes our recognition system user friendly.