  Optical Music Recognition (OMR) is an important and challenging area within
music information retrieval, the accurate detection of music symbols in digital
images is a core functionality of any OMR pipeline. In this paper, we introduce
a novel object detection method, based on synthetic energy maps and the
watershed transform, called Deep Watershed Detector (DWD). Our method is
specifically tailored to deal with high resolution images that contain a large
number of very small objects and is therefore able to process full pages of
written music. We present state-of-the-art detection results of common music
symbols and show DWD's ability to work with synthetic scores equally well as on
handwritten music.
