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This document presents a study on Facial Emotion Recognition (FER) using Convolutional Neural Networks (CNN) on the FER2013 dataset, achieving a validation accuracy of 63.25%. The model processes 35,887 grayscale images to classify them into seven emotional categories, utilizing data augmentation and a structured CNN architecture. Despite its lower accuracy compared to leading models, the study establishes a baseline for future improvements in FER systems.

Author

savanthvarshitha

Language

EN