Browsing Departament de Tecnologia by Subject "Deep learning"

Now showing items 1-2 of 2

    • Comparison of CNN-learned vs. handcrafted features for detection of Parkinson's disease dysgraphia in a multilingual dataset 

      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 (Frontiers in Neuroinformatics. 2022;(16):877139, 2022)
      Parkinson’s disease dysgraphia (PDYS), one of the earliest signs of Parkinson’s disease (PD), has been researched as a promising biomarker of PD and as the target of a noninvasive and inexpensive ...

    • On the analysis of speech and disfluencies for automatic detection of Mild Cognitive Impairment 

      López-de-Ipiña, Karmele; Martinez de lizarduy, Unai; Calvo, Paula M.; Beitia, Blanca; García Melero, J.; Fernández, E.; Ecay-Torres, Mirian; Faundez-Zanuy, Marcos; Sanz, P. (Neural Computing and Applications. 2020;32:15761–15769, 2018-05-08)
      Alzheimer’s disease is characterized by a progressive and irreversible cognitive deterioration. In a previous stage, the so-called Mild Cognitive Impairment or cognitive loss appears. Nevertheless, this ...