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A hybrid two-stage SqueezeNet and support vector machine system for Parkinson’s disease detection based on handwritten spiral patterns Cover

A hybrid two-stage SqueezeNet and support vector machine system for Parkinson’s disease detection based on handwritten spiral patterns

International Journal of Applied Mathematics and Computer Science
Volume 31 (2021): Issue 4 (December 2021)
By: Lucas Salvador Bernardo,  Robertas Damaševičius,  Victor Hugo C. De Albuquerque and  Rytis Maskeliūnas  
Open Access
|Dec 2021

Authors

Lucas Salvador Bernardo

lucas.salvador@ktu.edu

Department of Software Engineering, Kaunas University of Technology, Lithuania

Robertas Damaševičius

robertas.damasevicius@ktu.lt

Department of Software Engineering, Kaunas University of Technology, Lithuania

Victor Hugo C. De Albuquerque

victor.albuquerque@ieee.org

Department of Teleinformatics Engineering, Federal University of Ceara, Brazil

Rytis Maskeliūnas

rytis.maskeliunas@ktu.lt

Department of Multimedia Engineering, Kaunas University of Technology, Lithuania
DOI: https://doi.org/10.34768/amcs-2021-0037 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
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Language: English
Page range: 549 - 561
Submitted on: Jan 1, 2021
Accepted on: Sep 5, 2021
Published on: Dec 30, 2021
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Parkinson’s disease,
spirography,
convolutional neural network,
deep learning
Related subjects:
Mathematics,
Applied mathematics

© 2021 Lucas Salvador Bernardo, Robertas Damaševičius, Victor Hugo C. De Albuquerque, Rytis Maskeliūnas, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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