Name
Abstract | ||
|---|---|---|
This paper gives an overview of our current Optical Music Recognition (OMR) research. We recently released the OMR dataset emph{DeepScores} as well as the object detection method emph{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 task and tackling extreme class imbalance. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.21256/zhaw-4777 | arXiv: Computer Vision and Pattern Recognition |
Field | DocType | Volume |
Optical music recognition,Object detection,Computer science,Watershed,Artificial intelligence,Detector,Machine learning | Journal | abs/1810.05423 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ismail Elezi | 1 | 3 | 2.73 |
| Lukas Tuggener | 2 | 0 | 0.68 |
| Marcello Pelillo | 3 | 1888 | 150.33 |
| Thilo Stadelmann | 4 | 49 | 10.89 |