RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand
At a glance
- Co-project leader : Dr. Frank-Peter Schilling, Prof. Dr. Thilo Stadelmann
- Project team : Raphael Emberger, Adhiraj Ghosh, Dr. Javier Montoya, Pascal Sager, Yvan Putra Satyawan, Lukas Tuggener
- Project budget : CHF 870'000
- Project status : completed
- Funding partner : Innosuisse (Innovationsprojekt / Projekt Nr. 34301.1 IP-ICT)
- Contact person : Thilo Stadelmann
Description
ScorePad’s sheet music scanning service works for high quality input; to scale up business, it should work as well for smartphone pictures, used sheets etc. Project RealScore enhances the successful predecessor project by making deep learning adapt to unseen data through unsupervised learning.
Further information
Publications
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Tuggener, Lukas; Emberger, Raphael; Ghosh, Adhiraj; Sager, Pascal; Satyawan, Yvan Putra; Montoya, Javier; Goldschagg, Simon; Seibold, Florian; Gut, Urs; Ackermann, Philipp; Schmidhuber, Jürgen; Stadelmann, Thilo,
2023.
Real world music object recognition.
Transactions of the International Society for Music Information Retrieval.
Available from: https://doi.org/10.21256/zhaw-28719
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Tuggener, Lukas; Schmidhuber, Jürgen; Stadelmann, Thilo,
2022.
Is it enough to optimize CNN architectures on ImageNet?.
Frontiers in Computer Science.
4(1041703).
Available from: https://doi.org/10.3389/fcomp.2022.1041703
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Tuggener, Lukas; Satyawan, Yvan Putra; Pacha, Alexander; Schmidhuber, Jürgen; Stadelmann, Thilo,
2021.
The DeepScoresV2 dataset and benchmark for music object detection [paper].
In:
2020 25th International Conference on Pattern Recognition (ICPR).
25th International Conference on Pattern Recognition 2020 (ICPR’20), Online, 10-15 January 2021.
IEEE.
pp. 9188-9195.
Available from: https://doi.org/10.1109/ICPR48806.2021.9412290