All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Deep Learning Techniques for Classification of P300 Component

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43951149" target="_blank" >RIV/49777513:23520/18:43951149 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Deep Learning Techniques for Classification of P300 Component

  • Original language description

    Deep learning techniques have proved to be beneficial in many scientific disciplines and have beaten state-of-the-art approaches in many applications. The main aim of this article is to improve the success rate of deep learning algorithms, especially stacked autoencoders, when they are used for detection and classification of P300 event-related potential component that reflects brain processes related to stimulus evaluation or categorization. Moreover, the classification results provided by stacked autoencoders are compared with the classification results given by other classification models and classification results provided by combinations of various types of neural network layers

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    BIOSTEC 2018 Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies Volume 5: HEALTHINF

  • ISBN

    978-989-758-281-3

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    8

  • Pages from-to

    446-453

  • Publisher name

    SCITEPRESS – Science and Technology Publications

  • Place of publication

    Setúbal

  • Event location

    Madeira, Portugal

  • Event date

    Jan 19, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article