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A Perspective of the Noise Removal for Faster Neural Network Training

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU134020" target="_blank" >RIV/00216305:26220/19:PU134020 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/8970907" target="_blank" >https://ieeexplore.ieee.org/document/8970907</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICUMT48472.2019.8970907" target="_blank" >10.1109/ICUMT48472.2019.8970907</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Perspective of the Noise Removal for Faster Neural Network Training

  • Original language description

    Image classification is widely used within image processing area. It is known that insufficient amount of data has negative impact on the training of neural networks in terms of accuracy, convergence speed and in some cases even in the inability to converge. On the other hand, big amount of data significantly increases the training time and costs needed for model creation. Every training sample contains the part valuable for decision (face in case of this paper) and noise, i.e. background of the object. This paper introduces method of iterative noise removal during the training with combination with the transfer learning to optimize the speed of the training process. We show the combination of proposed noise removal and transfer learning leads to more effective training process and enables to learn also from limited data sets. The main contribution of this paper is a proposed method that reduces training time and it is able to accelerate the process in average by 69%. The method was tested on binary classification of two persons from LFW database.

  • 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

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>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

    2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

  • ISBN

    978-1-7281-5763-4

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    1-4

  • Publisher name

    Neuveden

  • Place of publication

    Dublin

  • Event location

    Dublin

  • Event date

    Oct 28, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000540651700047