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https://doi.org/10.21256/zhaw-4777| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | DeepScores and Deep Watershed Detection : current state and open issues |
| Authors: | Elezi, Ismail Tuggener, Lukas Pelillo, Marcello Stadelmann, Thilo |
| DOI: | 10.21256/zhaw-4777 |
| Proceedings: | Proceedings of the 1st International Workshop on Reading Music Systems |
| Page(s): | 13 |
| Pages to: | 14 |
| Conference details: | 1st International Workshop on Reading Music Systems at ISMIR 2018, Paris, France, 20 September 2018 |
| Issue Date: | 20-Sep-2018 |
| Publisher / Ed. Institution: | Society for Music Information Retrieval |
| Publisher / Ed. Institution: | Paris |
| Language: | English |
| Subjects: | Optical music recognition; Deep learning |
| Subject (DDC): | 006: Special computer methods |
| Abstract: | This paper gives an overview of our current Optical Music Recognition (OMR) research. We recently released the OMR data set DeepScores as well as the object detection method Deep Watershed Detector. We are currently taking some additional steps to improve both of them. Here we summarize current and future efforts, aimed at improving usefulness on real-world tasks and tackling extreme class imbalance. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/14488 |
| Fulltext version: | Published version |
| License (according to publishing contract): | CC BY-NC 4.0: Attribution - Non commercial 4.0 International |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Computer Science (InIT) |
| Published as part of the ZHAW project: | DeepScore: Digitales Notenpult mit musikalischem Verständnis durch Active Sheet Technologie |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Elezi_DeepScores and Deep Watershed Detection_WORMS_proceedings.pdf | 2.15 MB | Adobe PDF |  View/Open |
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Elezi, I., Tuggener, L., Pelillo, M., & Stadelmann, T. (2018). DeepScores and Deep Watershed Detection : current state and open issues [Conference paper]. Proceedings of the 1st International Workshop on Reading Music Systems, 13–14. https://doi.org/10.21256/zhaw-4777
Elezi, I. et al. (2018) ‘DeepScores and Deep Watershed Detection : current state and open issues’, in Proceedings of the 1st International Workshop on Reading Music Systems. Paris: Society for Music Information Retrieval, pp. 13–14. Available at: https://doi.org/10.21256/zhaw-4777.
I. Elezi, L. Tuggener, M. Pelillo, and T. Stadelmann, “DeepScores and Deep Watershed Detection : current state and open issues,” in Proceedings of the 1st International Workshop on Reading Music Systems, Sep. 2018, pp. 13–14. doi: 10.21256/zhaw-4777.
ELEZI, Ismail, Lukas TUGGENER, Marcello PELILLO und Thilo STADELMANN, 2018. DeepScores and Deep Watershed Detection : current state and open issues. In: Proceedings of the 1st International Workshop on Reading Music Systems. Conference paper. Paris: Society for Music Information Retrieval. 20 September 2018. S. 13–14
Elezi, Ismail, Lukas Tuggener, Marcello Pelillo, and Thilo Stadelmann. 2018. “DeepScores and Deep Watershed Detection : Current State and Open Issues.” Conference paper. In Proceedings of the 1st International Workshop on Reading Music Systems, 13–14. Paris: Society for Music Information Retrieval. https://doi.org/10.21256/zhaw-4777.
Elezi, Ismail, et al. “DeepScores and Deep Watershed Detection : Current State and Open Issues.” Proceedings of the 1st International Workshop on Reading Music Systems, Society for Music Information Retrieval, 2018, pp. 13–14, https://doi.org/10.21256/zhaw-4777.
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