Advancements in Facial Expression-Based Automatic Emotion Identification Using Deep Learning

Abstract

Facial expression-based automatic emotion identification is an intriguing research subject that has found applications in areas as diverse as security, healthcare, and the human-computer interface. Researchers in this area seek to improve computer prediction by creating methods for reading and encoding facial emotions. As deep learning has shown to be so effective, many designs have been used to maximize its potential. This paper's goal is to examine recent efforts towards fully autonomous FER with the use of deep learning. The researcher emphasizes these processing contributions, architectures and databases, and then illustrate the progress accomplished by comparing the offered approaches and acquired outcomes. This paper’s goal is to aid and direct scholars by surveying current efforts and offering suggestions for how to further the area.