Facial Emotion Recognition and Detection Using Convolutional Neural Networks

Abstract: Facial emotion recognition is a vital area within computer vision and artificial intelligence, with significant applications in human-computer interaction, security, and healthcare. This research presents a novel approach for identifying facial emotions through the use of Convolutional Neural Networks (CNNs). We provide a comprehensive overview of the CNN architecture, the dataset utilized, the preprocessing techniques employed, the training methodology, and the results achieved. Our approach demonstrates exceptional accuracy in detecting a range of emotions, including happiness, sadness, anger, and surprise. Additionally, this study explores the implications of our findings and suggests potential improvements and future research directions to enhance the performance and applicability of facial emotion recognition systems.