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@article{170569,
        author = {Prof. I. J. Shaikh and Archana C. Sargam and Archana P. Pagul and Krushnaveni N. Mhaisal and Lavanya N. Pola and Lavanya S. Sargam},
        title = {Handwritten-based Emotion Prediction System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {1285-1288},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170569},
        abstract = {This paper introduces a system designed to identify emotions through handwriting analysis. It examines features like slant, pressure, size, and spacing to provide insights into emotional states. Using machine learning, the system ensures privacy by not relying on facial or voice data. It offers real-time emotion detection, which is versatile and suitable for various applications such as mental health evaluation, personalized feedback, and educational assessments. The system overcomes limitations of traditional methods and ensures adaptability across diverse users.},
        keywords = {Emotion analysis, handwriting recognition, privacy-focused system, CNN Model.},
        month = {December},
        }