@Article{ArnauBaro2019,
author="Arnau Baro
and Pau Riba
and Jorge Calvo-Zaragoza
and Alicia Fornes",
title="From Optical Music Recognition to Handwritten Music Recognition: a Baseline",
journal="Pattern Recognition Letters",
year="2019",
volume="123",
pages="1--8",
abstract="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 handwritten 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.",
optnote="DAG; 600.097; 601.302; 601.330; 600.140; 600.121",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3275), last updated on Tue, 24 Nov 2020 10:15:22 +0100",
opturl="https://doi.org/10.1016/j.patrec.2019.02.029"
}