2022W

• Applied Deep Learning / 194.077 / VU

• Optical Music Recognition with Deep Learning
  2017 – 2020 / Universidad de Alicante

Note: Due to the rollout of TU Wien’s new publication database, the list below may be slightly outdated. Once APIs for the new database have been released, everything will be up to date again.

• The Challenge of Reconstructing Digits in Music Scores / A. Pacha / in: "Proceedings of the 3rd International Workshop on Reading Music Systems", J. Calvo-Zaragoza, A. Pacha (ed.); Proceedings of the 3rd International Workshop on Reading Music Systems, Alicante, Spain, 2021, 4 - 7
• Understanding Optical Music Recognition / J. Calvo-Zaragoza, J. Hajič, A. Pacha / Acm Computing Surveys, 53 (2020), 4
• The DeepScoresV2 Dataset and Benchmark for Music Object Detection / L. Tuggener, Y. Satyawan, A. Pacha, J. Schmidhuber, T. Stadelmann / in: "Proceedings of the 25th International Conference on Pattern Recognition 2020", 20; issued by: IAPR; Springer International Publishing, Milan, Italy, 2020, ISBN: 978-1-7281-8808-9, 9188 - 9195
• Identification and Cross-Document Alignment of Measures in Music Score Images / S. Waloschek, A. Pacha, A. Hadjakos / Talk: 20th International Society for Music Information Retrieval Conference, Delft, The Netherlands; 2019-11-04 - 2019-11-08; in: "20th International Society for Music Information Retrieval Conference", (2019), 137 - 143
• Learning Notation Graph Construction for Full-Pipeline Optical Music Recognition / A. Pacha, J. Calvo-Zaragoza, J. Hajič / Talk: 20th International Society for Music Information Retrieval Conference, Delft, The Netherlands; 2019-11-04 - 2019-11-08; in: "20th International Society for Music Information Retrieval Conference", (2019), 75 - 82
• Incremental Supervised Staff Detection / A. Pacha / Talk: 2nd International Workshop on Reading Music Systems, Delft, The Netherlands; 2019-11-02; in: "Proceedings of the 2nd International Workshop on Reading Music Systems", (2019), 16 - 20
• Self-Learning Optical Music Recognition / Doctoral Thesis by A. Pacha / Supervisor, Reviewer: H. Eidenberger, I. Fujinaga, O. Marques; Institute of Information Systems Engineering, 2019; oral examination: 2019-07-04
• Introduction to the MUSCIMA++ Dataset / J. Hajič, A. Pacha / Publication type: YouTube Video, project: Deep Learning for Optical Music Recognition; 2019
• How Current Optical Music Recognition Systems Are Becoming Useful for Digital Libraries / J. Hajič, M. Kolárová, A. Pacha, J. Calvo-Zaragoza / Talk: 5th International Conference on Digital Libraries for Musicology, Paris, France; 2018-09-28; in: "Proceedings of the 5th International Conference on Digital Libraries for Musicology", (2018), 57 - 61
• Optical Music Recognition for Dummies / J. Calvo-Zaragoza, J. Hajič, A. Pacha, I. Fujinaga / Keynote Lecture: 19th International Society for Music Information Retrieval Conference, Paris, France; 2018-09-23 - 2018-09-27
• Optical Music Recognition in Mensural Notation with Region-Based Convolutional Neural Networks / A. Pacha, J. Calvo-Zaragoza / Talk: 19th International Society for Music Information Retrieval Conference, Paris, France; 2018-09-23 - 2018-09-27; in: "Proceedings of the 19th International Society for Music Information Retrieval Conference", (2018), 240 - 247
• Advancing OMR as a Community: Best Practices for Reproducible Research / A. Pacha / Talk: 1st International Workshop on Reading Music Systems, Paris, France; 2018-09-20; in: "Proceedings of the 1st International Workshop on Reading Music Systems", (2018), 19 - 20
• Self-Learning Optical Music Recognition / A. Pacha / Talk: Vienna young Scientists Symposium, Wien; 2018-06-07 - 2018-06-08; in: "Vienna young Scientists Symposium", Book-of-Abstracts.com, (2018), ISBN: 978-3-9504017-8-3; 34 - 35
• Handwritten Music Object Detection: Open Issues and Baseline Results / A. Pacha, K. Choi, B. Coüasnon, Y. Ricquebourg, H. Eidenberger / Talk: 2018 13th IAPR Workshop on Document Analysis Systems (DAS), Wien; 2018-04; in: "2018 13th IAPR Workshop on Document Analysis Systems (DAS)", (2018), 6 pages
• A Baseline for General Music Object Detection with Deep Learning / A. Pacha, J. Hajič, J. Calvo-Zaragoza / Applied Sciences, 8 (2018), 9; 1488 - 1508
• Discussion Group Summary: Optical Music Recognition / J. Calvo-Zaragoza, J. Hajič, A. Pacha / in: "Graphics Recognition. Current Trends and Evolutions", A. Fornés, B. Lamiroy (ed.); Springer International Publishing, Cham, 2018, (invited), ISBN: 978-3-030-02284-6, 152 - 157
• Towards Self-Learning Optical Music Recognition / A. Pacha, H. Eidenberger / Talk: 16th IEEE International Conference on Machine Learning and Applications, Cancun; 2017-12-18 - 2017-12-21; in: "2017 16th IEEE International Conference on Machine Learning and Applications", (2017), 6 pages
• Towards a Universal Music Symbol Classifier / A. Pacha, H. Eidenberger / Talk: International Workshop on Graphics Recognition, New York; 2017-11-09 - 2017-11-10; in: "Proceedings of the 12th International Workshop on Graphics Recognition", (2017), ISBN: 978-1-5386-3586-5; 2 pages
• Quality Assurance for Data from Low-Tech Participants in Distributed Automation Engineering Environments / R. Mordinyi, A. Pacha, S. Biffl / Talk: 16th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2011), Toulouse, France; 2011-09-05 - 2011-09-09; in: "Proceeding of 16th IEEE International Conference on Emerging Technologies and Factory Automation", Z. Mammeri (ed.); (2011), ISBN: 978-1-4577-0018-7; 1 - 4