Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: In: Frontiers in Neuroinformatics 16 (2022): 877139.

Event: Veröffentlichung

(where): Erlangen

(who): Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

(when): 2022

Creator: Galaz, Zoltan
Drotar, Peter
Mekyska, Jiri
Gazda, Matej
Mucha, Jan
Zvoncak, Vojtech
Smekal, Zdenek
Faundez-Zanuy, Marcos
Castrillon, Reinel
Orozco-Arroyave, Juan Rafael
Rapcsak, Steven
Kincses, Tamas
Brabenec, Lubos
Rektorova, Irena

DOI: 10.3389/fninf.2022.877139

URN: urn:nbn:de:bvb:29-opus4-196232

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:33 AM CEST

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Associated

Galaz, Zoltan
Drotar, Peter
Mekyska, Jiri
Gazda, Matej
Mucha, Jan
Zvoncak, Vojtech
Smekal, Zdenek
Faundez-Zanuy, Marcos
Castrillon, Reinel
Orozco-Arroyave, Juan Rafael
Rapcsak, Steven
Kincses, Tamas
Brabenec, Lubos
Rektorova, Irena
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

Time of origin

2022

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Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset

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