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A new perceptual evaluation method of video quality based on neural network

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248276" target="_blank" >RIV/61989100:27240/21:10248276 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/21:10248276

  • Result on the web

    <a href="https://content.iospress.com/articles/intelligent-data-analysis/ida205085" target="_blank" >https://content.iospress.com/articles/intelligent-data-analysis/ida205085</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3233/IDA-205085" target="_blank" >10.3233/IDA-205085</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A new perceptual evaluation method of video quality based on neural network

  • Original language description

    This paper proposes a novel method for video quality evaluation based on machine learning technique. The current research deals with the correct interpretation of objective video quality evaluation (Quality of Service - QoS) in relation to subjective end-user perception (Quality of Experience - QoE), typically expressed by mean opinion score (MOS). Our method allows us to interconnect results obtained from video objective and subjective assessment methods in the form of a neural network (computing model inspired by biological neural networks). So far, no unified interpretation scale has been standardized for both approaches, therefore it is difficult to determine the level of end-user satisfaction obtained from the objective assessment. Thus, contribution of the proposed method lies in description of the way to create a hybrid metric that delivers fast and reliable subjective score of perceived video quality for internet television (IPTV) broadcasting companies.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

    <a href="/en/project/LM2018140" target="_blank" >LM2018140: e-Infrastructure CZ</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Intelligent Data Analysis

  • ISSN

    1088-467X

  • e-ISSN

  • Volume of the periodical

    25

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    17

  • Pages from-to

    571-587

  • UT code for WoS article

    000644439500006

  • EID of the result in the Scopus database