Residual Recurrent CRNN for End-to-End Optical Music Recognition on Monophonic Scores
Author:
Affiliation:
1. Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, China
2. University of London, London, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3463945.3469056
Reference21 articles.
1. Recognition of Handwritten Music Symbols with Convolutional Neural Codes
2. Jorge Calvo-Zaragoza and David Rizo. 2018. Camera-PrIMuS: Neural End-to-End Optical Music Recognition on Realistic Monophonic Scores.. In ISMIR. 248--255. Jorge Calvo-Zaragoza and David Rizo. 2018. Camera-PrIMuS: Neural End-to-End Optical Music Recognition on Realistic Monophonic Scores.. In ISMIR. 248--255.
3. End-to-End Neural Optical Music Recognition of Monophonic Scores
4. Pixel-wise binarization of musical documents with convolutional neural networks
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