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ZENODO
Dataset . 2024
License: CC BY SA
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY SA
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY SA
Data sources: Datacite
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Handwritten Opera OMR

Authors: Simonetta, Federico; Mondal, Rishav; Ludovico, Luca Andrea; Ntalampiras, Stavros;

Handwritten Opera OMR

Abstract

This repository contains the dataset of more than 198.000 small images extracted from handwritten music scores of the Archivio Storico Ricordi and organized for optical music recognition (OMR) research. The images are categorized in 11 classes (multiclass task) or 2 classes (binary task). In the download there is also the code used for annotating and analyzing the dataset, as well as the model weights resulting from training. Additional information is available in the paper (under review). Cite us Simonetta F., Mondal R., Ludovico L. A., Ntalampiras S. "Optical Music Recognition in Manuscripts from the Ricordi Archive", AudioMostly 2024, Milan, Italy. DOI: https://doi.org/10.1145/3678299.3678324

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average