Explainable AI in Handwriting Detection for Dyslexia Using Transfer Learning

• URL: http://arxiv.org/abs/2410.19821v2
• Date: Tue, 17 Dec 2024 22:40:26 GMT
• Title: Explainable AI in Handwriting Detection for Dyslexia Using Transfer Learning
• Authors: Mahmoud Robaa, Mazen Balat, Rewaa Awaad, Esraa Omar, Salah A. Aly,
• Abstract summary: The framework integrates transfer learning and transformer-based models, identifying handwriting features associated with dyslexia. Its adaptability to different languages and writing systems underscores its potential for global applicability. The findings emphasize the framework's ability to support early detection, build stakeholder trust, and enable personalized educational strategies.
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• Abstract: This study introduces an explainable AI (XAI) framework for the detection of dyslexia through handwriting analysis, achieving an impressive test precision of 99.65%. The framework integrates transfer learning and transformer-based models, identifying handwriting features associated with dyslexia while ensuring transparency in decision-making via Grad-CAM visualizations. Its adaptability to different languages and writing systems underscores its potential for global applicability. By surpassing the classification accuracy of state-of-the-art methods, this approach demonstrates the reliability of handwriting analysis as a diagnostic tool. The findings emphasize the framework's ability to support early detection, build stakeholder trust, and enable personalized educational strategies.

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