Deep Learning Approach for Facial Expression Recognition

Abstract

Abstract: In recent decades, facial expression recognition has emerged as a hot topic with significant implications in the realm of human-computer interaction. The simplest way for humans to express their emotions is through facial expressions. Non-verbal communication relies heavily on facial expression. This study outlines deep learning-based Facial Expression Recognition (FER) algorithm. The performance of the FER approach is compared based on the number of expressions detected and the difficulty of CNN algorithms. The FER2013, CK+ databases were used in testing the design. CNNs (Convolutional Neural Networks) have as of late gained fame in the field of profound learning because of its superb plan and capacity to convey clever outcomes without the requirement for manual feature extraction from raw information. The suggested algorithm achieves a higher rate of recognition on four datasets.