Classification of optical music symbols based on combined neural network

dc.contributor.author Wen,C en
dc.contributor.author Ana Maria Rebelo en
dc.contributor.author Zhang,J en
dc.contributor.author Jaime Cardoso en
dc.date.accessioned 2018-01-21T21:13:36Z
dc.date.available 2018-01-21T21:13:36Z
dc.date.issued 2014 en
dc.description.abstract In this paper, a new method for music symbol classification named Combined Neural Network (CNN) is proposed. Tests are conducted on more than 9000 music symbols from both real and scanned music sheets, which show that the proposed technique offers superior classification capability. At the same time, the performance of the new network is compared with the single Neural Network (NN) classifier using the same music scores. The average classification accuracy increased more than ten percent, reaching 98.82%. © 2014 IEEE. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/7205
dc.identifier.uri http://dx.doi.org/10.1109/icmc.2014.7231590 en
dc.language eng en
dc.relation 3889 en
dc.relation 4884 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Classification of optical music symbols based on combined neural network en
dc.type conferenceObject en
dc.type Publication en
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