RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand
Auf einen Blick
- Co-Projektleiter/in : Dr. Frank-Peter Schilling, Prof. Dr. Thilo Stadelmann
- Projektteam : Raphael Emberger, Adhiraj Ghosh, Dr. Javier Montoya, Pascal Sager, Yvan Putra Satyawan, Lukas Tuggener
- Projektvolumen : CHF 870'000
- Projektstatus : abgeschlossen
- Drittmittelgeber : Innosuisse (Innovationsprojekt / Projekt Nr. 34301.1 IP-ICT)
- Projektpartner : ScorePad AG
- Kontaktperson : Thilo Stadelmann
Beschreibung
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.
Weiterführende Informationen
Publikationen
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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,
2024.
Real world music object recognition.
Transactions of the International Society for Music Information Retrieval.
7(1), S. 1-14.
Verfügbar unter: https://doi.org/10.5334/tismir.157
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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).
Verfügbar unter: 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.
S. 9188-9195.
Verfügbar unter: https://doi.org/10.1109/ICPR48806.2021.9412290