Facial Emotion Recognition

Facial emotion recognition (FER) aims to automatically identify human emotions from facial expressions, leveraging computer vision techniques to understand nonverbal communication. Current research emphasizes improving accuracy and generalization across diverse datasets and populations, often employing deep learning architectures like convolutional neural networks (CNNs), transformers, and hybrid models that incorporate contextual information or multimodal data. This field is significant for its potential applications in various domains, including human-computer interaction, mental health assessment, and personalized education, while also raising important ethical considerations regarding bias and fairness in algorithms.