A Convolutional Recurrent Neural Network-Based Model For Handwritten Text Recognition To Predict Dysgraphia-Reference-Cited by-同舟云学术

A Convolutional Recurrent Neural Network-Based Model For Handwritten Text Recognition To Predict Dysgraphia

Published:2023-02-09 Issue: Volume: Page:
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Container-title:2023 International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS)
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Author:

Doshi Neha N.¹,Maniyar Manali U.¹,Shah Khushi K.¹,Sarda Namrata D.¹,Narvekar Meera¹,Mukhopadhyay Debajyoti²

Affiliation:

1. Department of Computer Engineering, DJSCE,Mumbai,India

2. WIDiCoReL Lab,Department of Computer Engineering,Mumbai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099476/10100336/10100514.pdf?arnumber=10100514

Reference10 articles.

1. Dyslexia and Dysgraphia prediction: A new machine learning approach;richard;ArXiv,2020

2. DysLexML: Screening Tool for Dyslexia Using Machine Learning;asvestopoulou;ArXiv,2019

3. Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree;david;(IJCSIT) International Journal of Computer Science and Information Technologies,2011

4. Towards Detecting Dyslexia in Children's Handwriting Using Neural Networks;spoon;ICML Workshop on AI for Social Good,2019

5. Evaluation of Digitalized Handwriting for Dysgraphia Detection Using Random Forest Classification Method

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