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Adaptive polynomial filters with individual learning rates for computationally efficient lung tumor motion prediction

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F15%3A00236641" target="_blank" >RIV/68407700:21220/15:00236641 - isvavai.cz</a>

  • Result on the web

    <a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7347077" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7347077</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/IWCIM.2015.7347077" target="_blank" >10.1109/IWCIM.2015.7347077</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Adaptive polynomial filters with individual learning rates for computationally efficient lung tumor motion prediction

  • Original language description

    This paper presents a study of higher-order neural units as polynomial adaptive filters with multiple-learning-rate gradient descent for 3-D lung tumor motion prediction. The method is compared with single-learning rate gradient descent approaches with and without learning rate normalization. Experimental analysis is done with linear and quadratic neural unit. The influence of correct selection of adaptation parameters and the dependence of learning time on accuracy were experimentally analyzed. The prediction accuracy is nearly equal to recently published results of batch retraining approaches while the computational efficiency is higher for the introduced approach.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BC - Theory and management systems

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE FOR MULTIMEDIA UNDERSTANDING

  • ISBN

    978-1-4673-8457-5

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

  • Publisher name

    České vysoké učení technické v Praze

  • Place of publication

    Praha

  • Event location

    Praha

  • Event date

    Oct 29, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000380431200017