RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand
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.
Eckdaten
Co-Projektleitung
Projektteam
Lukas Tuggener, Yvan Putra Satyawan, Raphael Emberger, Adhiraj Ghosh, Pascal Sager, Dr. Javier Montoya
Projektpartner
ScorePad AG
Projektstatus
abgeschlossen, 09/2019 - 05/2022
Institut/Zentrum
Institut für Informatik (InIT); Centre for Artificial Intelligence (CAI)
Drittmittelgeber
Innovationsprojekt / Projekt Nr. 34301.1 IP-ICT
Projektvolumen
870'000 CHF
Weiterführende Dokumente und Links
Publikationen
-
Efficient rotation invariance in deep neural networks through artificial mental rotation
2025 Tuggener, Lukas; Stadelmann, Thilo; Schmidhuber, Jürgen
-
Real world music object recognition
2024 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
-
Is it enough to optimize CNN architectures on ImageNet?
2022 Tuggener, Lukas; Schmidhuber, Jürgen; Stadelmann, Thilo
-
The DeepScoresV2 dataset and benchmark for music object detection
2021 Tuggener, Lukas; Satyawan, Yvan Putra; Pacha, Alexander; Schmidhuber, Jürgen; Stadelmann, Thilo
Forschungsdaten
School of Engineering
Technikumstrasse 71
8400 Winterthur