4.5 Article

From Optical Music Recognition to Handwritten Music Recognition: A baseline

期刊

PATTERN RECOGNITION LETTERS
卷 123, 期 -, 页码 1-8

出版社

ELSEVIER
DOI: 10.1016/j.patrec.2019.02.029

关键词

Optical music recognition; Handwritten music recognition; Document image analysis and recognition; Deep neural networks; LSTM

资金

  1. Spanish project [TIN2015-70924-C2-2-R]
  2. CERCA Program/Generalitat de Catalunya
  3. FPU fellowship [FPU15/06264]
  4. Ramon y Cajal Fellowship [RYC-2014-16831]
  5. FI fellowship (Secretaria d'Universitats i Recerca of the Generalitat de Catalunya) [AGAUR 2018 FI_B 00546]
  6. FI fellowship (Fons Social Europeu) [AGAUR 2018 FI_B 00546]
  7. NVIDIA Corporation

向作者/读者索取更多资源

Optical Music Recognition (OMR) is the branch of document image analysis that aims to convert images of musical scores into a computer-readable format. Despite decades of research, the recognition of hand-written music scores, concretely the Western notation, is still an open problem, and the few existing works only focus on a specific stage of OMR. In this work, we propose a full Handwritten Music Recognition (HMR) system based on Convolutional Recurrent Neural Networks, data augmentation and transfer learning, that can serve as a baseline for the research community. (C) 2019 Elsevier B.V. All rights reserved.

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