Browsing by Author "Douaa Hanan, Kadi"

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    Facial Emotion Recognition Using Deep Learning Approach
    (Mohamed Boudiaf University of M'sila, 2025-06-15) Douaa Hanan, Kadi; Nada Erayhane, Heltali; Supervisor: Said, Gadri
    This thesis aims to design and implement a system for recognizing human emotions based on facial expressions, using artificial intelligence techniques, particularly Convolutional Neural Networks (CNN). Emotion recognition is an emerging and important field within affective computing, with broad applications in mental health, education, marketing, surveillance systems, and human-computer interaction. In this work, a facial image dataset containing various emotions (such as anger, happiness, sadness, surprise...) was used. The images underwent preprocessing steps such as grayscale conversion and resizing. The CNN model was then trained using environments like JupyterLab and Google Colab, with tools such as TensorFlow and Keras used for model design and evaluation. The system consisted of the following main stages:  Face Detection  Feature Extraction  Emotion Classification The results showed good accuracy in emotion recognition, confirming the effectiveness of the proposed model. A simple application interface was also developed to test the model on both live and stored images, bringing the project closer to real-world applications. Despite the promising results, some challenges remain, such as lighting conditions, facial angle variations, and similarities between emotional expressions. This opens the door for more advanced future work, such as integrating multiple modalities (voice, text, facial expression) or adopting more powerful models trained on more diverse datasets.