Facial emotion recognition with machine learning

Abstract

This work is describing the fundamentals of machine learning and artificial neural networks. It introduces the functionality of different layers in a conventional neural network and different approaches to machine learning. With the help of conventional neural networks, a program is created where a model will be trained on a neural network to detect 5 facial emotions in a real-time video camera. It uses python programming language with powerful libraries like Keras and TensorFlow. This work aims to show the new technologies like transfer learning that can help to achieve better performance and accuracy.