"Comparison of CNN-Learned vs. Handcrafted Features for Detection of ..."

Zoltan Galaz et al. (2022)

> Home

Details and statistics

DOI: 10.3389/FNINF.2022.877139

access: open

type: Journal Article

metadata version: 2025-03-03

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/fini/GalazDMGMZSFCOR22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/fini/GalazDMGMZSFCOR22
Zoltan Galaz, Peter Drotár, Jirí Mekyska, Matej Gazda, Jan Mucha, Vojtech Zvoncak, Zdenek Smékal, Marcos Faúndez-Zanuy, Reinel Castrillon, Juan Rafael Orozco-Arroyave, Steven Z. Rapcsak, Tamas Kincses, Lubos Brabenec, Irena Rektorová:
Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset. Frontiers Neuroinformatics 16: 877139 (2022)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.