TensorFlow model to perform end-to-end Optical Music Recognition on monophonic scores through Convolutional Recurrent Neural Networks and CTC-based training.
@Article{Calvo-Zaragoza2018,
AUTHOR = {Calvo-Zaragoza, Jorge and Rizo, David},
TITLE = {End-to-End Neural Optical Music Recognition of Monophonic Scores},
JOURNAL = {Applied Sciences},
VOLUME = {8},
YEAR = {2018},
NUMBER = {4},
ARTICLE NUMBER = {606},
URL = {http://www.mdpi.com/2076-3417/8/4/606},
ISSN = {2076-3417},
DOI = {10.3390/app8040606}
}
This repository is intended for the Printed Images of Music Staves (PrIMuS) dataset.
The source code used to generate the models, and examples on how to use it, can be found at
https://github.com/MasonDill/tf-end-to-end
These models were the result of the traning process for one of the folds of the 10-fold cross-validation considered in the paper.
This sample belongs to the test set of the aforementioned fold, so it was not seen by the networks during their training stage.