CNN-Based Handwriting Analysis for the Prediction of Autism Spectrum Disorder
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-35308-6_14
Reference18 articles.
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2. Moetesum, M., Siddiqi, I., Vincent, N., Cloppet, F.: Assessing visual attributes of handwriting for prediction of neurological disorders-A case study on Parkinson’s disease. Pattern Recogn. Lett. 121, 19–27 (2019)
3. Gornale, S., Kumar, S., Siddalingappa, R., Hiremath, P.S.: Survey on handwritten signature biometric data analysis for assessment of neurological disorder using machine learning techniques. Trans. Mach. Learn. Artif. Intell. 10, 27–60 (2022)
4. Faundez-Zanuy, M., Fierrez, J., Ferrer, M.A., Diaz, M., Tolosana, R., Plamondon, R.: Handwriting biometrics: applications and future trends in e-security and e-health. Cogn. Comput. 12, 940–953 (2020)
5. Rosenblum, S., Ben-Simhon, H.A., Meyer, S., Gal, E.: Predictors of handwriting performance among children with autism spectrum disorder. Res. Autism Spectrum Disorders 60, 16–24 (2019)
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1. A Review on Autism Spectrum Disorder Screening by Artificial Intelligence Methods;Journal of Autism and Developmental Disorders;2024-06-06
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