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@article{179096,
        author = {HARSHITHA N C and Dr.J V Gorabal and Chandana D G and Dhruva Kumar C and Bhoomika G N},
        title = {Real Time Facial Emotion Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7302-7304},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179096},
        abstract = {Facial emotion recognition (FER) is a critical area of research with applications spanning from human-computer interaction to security and healthcare. This project presents a novel Realtime facial emotion recognition system using deep learning techniques (1), our approach accurately shows and classifies human emotions from live video feeds (1). The proposed system integrates preprocessing steps including face detection and alignment, followed by emotion classification using a deep neural network model trained on a comprehensive dataset. Extensive experiments prove the system’s high accuracy and robustness in varied conditions and with diverse facial expressions. Our results write down that the proposed method outperforms existing state-of-the- art FER systems in both speed and accuracy, making it suitable for real- world applications (1). This dataset consists of 48x48 sized face images with seven emotions - angry, disgusted, fear, happy, neutral, sad, and surprised. Index Terms—Deep learning, facial emotion recognition, human computer interaction, real-time system.},
        keywords = {},
        month = {May},
        }