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Learning Robust Features for Gait Recognition by Maximum Margin Criterion

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00091550" target="_blank" >RIV/00216224:14330/16:00091550 - isvavai.cz</a>

  • Result on the web

    <a href="http://link.springer.com/content/pdf/bbm%3A978-3-319-49055-7%2F1.pdf" target="_blank" >http://link.springer.com/content/pdf/bbm%3A978-3-319-49055-7%2F1.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-49055-7" target="_blank" >10.1007/978-3-319-49055-7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Learning Robust Features for Gait Recognition by Maximum Margin Criterion

  • Original language description

    Extended abstract. The full research paper "Learning Robust Features for Gait Recognition by Maximum Margin Criterion" has been accepted for publication at the 23rd IEEE/IAPR International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, December 2016.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • 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 the joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2016) and Statistical Techniques in Pattern Recognition (SPR 2016)

  • ISBN

    9783319490540

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    2

  • Pages from-to

    585-586

  • Publisher name

    Springer International Publishing AG

  • Place of publication

    Switzerland

  • Event location

    Mérida, Mexico

  • Event date

    Jan 1, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000389509300052