Deep Learning Based Facial Emotion Recognition & Intelligent Facial Affect Detection

Abstract: Facial Emotion Recognition (FER) plays a crucial role in human-computer interaction, enabling machines to interpret human emotions effectively. With the advancement of deep learning techniques, significant improvements have been achieved in recognizing facial expressions with higher accuracy. This paper presents a deep learning-based approach for facial emotion recognition and intelligent facial affect detection using Convolutional Neural Networks (CNNs). The proposed system analyzes facial features from images and classifies emotions such as happiness, sadness, anger, surprise, fear, and neutral. The study evaluates performance using benchmark datasets and demonstrates improved accuracy compared to traditional machine learning methods. Applications include healthcare, security, education, and human-computer interaction systems.

Keywords: Facial Emotion Recognition, Deep Learning, CNN, Computer Vision, Affect Detection, Artificial Intelligence.