Abstract :

Emotion recognition is a rapidly growing research area in artificial intelligence that focuses on identifying human emotional states using computational techniques. Human emotions play a vital role in communication, decision-making, and behavior analysis. With advancements in deep learning, emotion recognition systems have achieved significant improvements in accuracy and robustness. This project presents an emotion recognition system using deep learning models trained on facial expression datasets. The system processes facial images to extract discriminative features automatically without manual feature engineering. Convolutional Neural Networks (CNNs) are used to learn spatial features that represent various emotions such as happiness, sadness, anger, fear, surprise, disgust, and neutrality. The proposed system includes preprocessing, face detection, feature extraction, and emotion classification stages. The model is trained and evaluated using benchmark datasets to ensure reliabilit