In recent years, foundation models (FMs) such as large language models (LLMs) and latent
diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This …

Optical Music Recognition (OMR) is concerned with transcribing sheet music into a machine-readable
format. The transcribed copy should allow musicians to compose, play and edit …

Optical Music Recognition (OMR) automates the transcription of musical notation from
images into machine-readable formats like MusicXML, MEI, or MIDI, significantly reducing the …

The generation of handwritten music sheets is a crucial step toward enhancing Optical
Music Recognition (OMR) systems, which rely on large and diverse datasets for optimal …

The main challenges of Optical Music Recognition (OMR) come from the nature of written
music, its complexity and the difficulty of finding an appropriate data representation. This paper …

There have been significant breakthroughs in computer vision research in many subfields,
including composer identification from images of sheet music. Previous work in composer …

In this paper, we explore the intersection of technology and cultural preservation by
developing a self-supervised learning framework for the classification of musical symbols in …

In optical music recognition (OMR), the scarcity of handwritten music sheet datasets limits
technological advancement. Addressing this, our study introduces a method to synthetically …

Data preprocessing techniques are frequently employed to address a model’s generalisation
capability and performance constraints due to the quality and diversity of its training data. …

Fake news articles are differently written, depending on the type, motivation and writing style.
Previous work in deception detection in fake news use features that are manually made …