AI-Powered Emotion Interpretation from Facial Cues using Deep Learning Techniques

Facial emotion detection plays a crucial role in understanding human behavior and has gained major consideration in several domains, including education. This research intends an automated method for facial emotion detection of students using deep learning techniques. This work leverages deep learning model, explicitly the model known as Convolutional Neural Networks (CNNs), which extract significant features from images of human face. The models are trained to classify emotions into commonly recognized kinds, such as happiness, anger, sadness, surprise, fear, and disgust. This work aims to provide a valuable tool for educators and researchers to objectively assess students' emotional states and tailor educational interventions accordingly. By understanding students' emotional responses, educators can identify areas where students may require additional support, personalize their teaching strategies, and create a positive and engaging learning environment.