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Multi-modal image search for large-scale applications

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F12%3A00073207" target="_blank" >RIV/00216224:14330/12:00073207 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Multi-modal image search for large-scale applications

  • Original language description

    One of the major challenges of data processing is the efficient multi-modal searching in large collections of complex data objects. In this paper, we present first results of a complex study that focuses on a comparison of various image retrieval methodsin terms of effectiveness, efficiency, and scalability. We introduce a classification of possible approaches, outline the methodology used for evaluation, and present results of our first experiments.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/VF20102014004" target="_blank" >VF20102014004: Multimedia Analysis</a><br>

  • Continuities

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

Others

  • Publication year

    2012

  • 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 International Workshop on Multimedia Databases and Data Engineering

  • ISBN

    9888889990

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    1-7

  • Publisher name

    VLDB Endowment

  • Place of publication

    Istanbul

  • Event location

    Instanbul, Turecko

  • Event date

    Aug 31, 2012

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article