Dysgraphia detection through machine learning
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Updated
Dec 14, 2020
Dysgraphia detection through machine learning
Research Methods and Tools
Math Typing Application for those with Learning Disabilities
A Django App designed for those with dysgraphia. This is a part of a project currently being worked on as a part of the College curriculum.
Your handwriting your vision language model
Developed a Dysgraphia Detection web app using React, Flask, and TensorFlow to detect dysgraphia from handwriting samples. Built a CNN-BiLSTM model achieving 91% accuracy and provided structured reports for user-friendly diagnosis.
Computer Science final project - correcting spelling mistakes in hebrew handwritings (deprecated)
Bachelor Thesis in Computer Science and Engineering at University of Florence titled "Neural Networks for handwriting analysis with smart-pen".
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