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How to Exploit Music Notation Syntax for OMR?

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372149" target="_blank" >RIV/00216208:11320/17:10372149 - isvavai.cz</a>

  • Result on the web

    <a href="http://doi.org/10.1109/ICDAR.2017.275" target="_blank" >http://doi.org/10.1109/ICDAR.2017.275</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICDAR.2017.275" target="_blank" >10.1109/ICDAR.2017.275</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    How to Exploit Music Notation Syntax for OMR?

  • Original language description

    A major roadblock for Optical Music Recognition, especially for handwritten music notation, is symbol detection: recovering the locations of musical symbols from the input page. This has been attempted both with bottom-up approaches exploiting visual features, and top-down approaches based on the strong constraints that music notation syntax imposes on possible symbol configurations; sometimes joined together at appropriate points in the recognition process. The bottom-up approach has recently greatly improved with the boom of neural networks. However, the reduction in uncertainty that music notation syntax can provide has not yet been married to the power of these neural network models. This extended abstract brainstorms ways in which this can be done, and analyzes the difficulties the various combined approaches will have to address. We hope our work will foster further discussion to clarify the issues involed, provoke OMR researchers to try some of these approaches experimentally, and entice resear

  • 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

    <a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>

  • Continuities

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

Others

  • Publication year

    2017

  • 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 12th IAPR International Workshop on Graphics Recognition

  • ISBN

    978-1-5386-3586-5

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    2

  • Pages from-to

    55-56

  • Publisher name

    IEEE Computer Society

  • Place of publication

    New York, USA

  • Event location

    Kyoto, Japan

  • Event date

    Nov 9, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article