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Microwave stroke detection and classification using different methods from MATLAB's classification learner toolbox

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F19%3A00334943" target="_blank" >RIV/68407700:21460/19:00334943 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Microwave stroke detection and classification using different methods from MATLAB's classification learner toolbox

  • Original language description

    In this work, performance of 5 different supervised learning algorithms from MATLAB Classification learner toolbox for microwave stroke detection and classification was tested and the suitability of the algorithms were compared. For this purpose, training and test data were obtained using a 2D microwave imaging system and reconfigurable head phantom.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of European Microwave Conference in Central Europe, EuMCE 2019

  • ISBN

    9782874870675

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    500-503

  • Publisher name

    European Microwave Association (EuMA)

  • Place of publication

    Louvain-la-Neuve

  • Event location

    Praha

  • Event date

    May 13, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article