For over 50 years, researchers have been trying to teach computers to read music notation,
referred to as Optical Music Recognition (OMR). However, this field is still difficult to access …

Deep learning is bringing breakthroughs to many computer vision subfields including
Optical Music Recognition (OMR), which has seen a series of improvements to musical …

Staff-line removal is an important preprocessing stage as regards most Optical Music
Recognition systems. The common procedures employed to carry out this task involve …

In this work, we present an approach for the task of optical music recognition (OMR) using
deep neural networks. Our intention is to simultaneously detect and categorize musical …

This study is a call for action for the music information retrieval (MIR) community to pay more
attention to collaboration with digital music archives. The study, which resulted from an …

Music is a key element for cultural transmission, and so large collections of music
manuscripts have been preserved over the centuries. In order to develop computational …

In this paper, we present a hybrid approach using hidden Markov models (HMM) and
artificial neural networks to deal with the task of handwritten Music Recognition in mensural …

Pitch-class distributions (PCDs) are fundamental objects of study in many fields of empirical
music research, from music information retrieval (MIR), mathematical music theory, and …

There are large collections of music manuscripts preserved over the centuries. In order to
analyze these documents it is necessary to transcribe them into a machine-readable format …

Optical Music Recognition (OMR) promises to make large collections of sheet music
searchable by their musical content. It would open up novel ways of accessing the vast …