@InProceedings{ArnauBaro2018,
author="Arnau Baro
and Pau Riba
and Alicia Fornes",
title="A Starting Point for Handwritten Music Recognition",
booktitle="1st International Workshop on Reading Music Systems",
year="2018",
pages="5--6",
optkeywords="Optical Music Recognition",
optkeywords="Long Short-Term Memory",
optkeywords="Convolutional Neural Networks",
optkeywords="MUSCIMA++",
optkeywords="CVCMUSCIMA",
abstract="In the last years, the interest in Optical Music Recognition (OMR) has reawakened, especially since the appearance of deep learning. However, there are very few works addressing handwritten scores. In this work we describe a full OMR pipeline for handwritten music scores by using Convolutional and Recurrent Neural Networks that could serve as a baseline for the research community.",
optnote="DAG; 600.097; 601.302; 601.330; 600.121",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3223), last updated on Thu, 28 Mar 2019 10:18:09 +0100",
file=":http://refbase.cvc.uab.es/files/BRF2018.pdf:PDF"
}