Face Expression Detection

This project focuses on building a robust facial expression detection system using Convolutional Neural Networks (CNNs). By leveraging deep learning, the model identifies emotions like happiness, sadness, anger, and surprise from facial images. Data augmentation techniques such as rotation, flipping, scaling, and brightness adjustments are applied to enhance the diversity of the training dataset, improving model generalization and performance. The system processes facial inputs, predicts expressions with high accuracy, and is suitable for applications in human-computer interaction, sentiment analysis, and behavioral studies.