Search Results for author: Elona Shatri

Found 6 papers, 3 papers with code

Knowledge Discovery in Optical Music Recognition: Enhancing Information Retrieval with Instance Segmentation

no code implementations27 Aug 2024 Elona Shatri, George Fazekas

This study emphasises the role of pixel-wise segmentation in advancing accurate music symbol recognition, contributing to knowledge discovery in OMR.

Information Retrieval Instance Segmentation +7

Proceedings of the 5th International Workshop on Reading Music Systems

1 code implementation7 Nov 2023 Jorge Calvo-Zaragoza, Alexander Pacha, Elona Shatri

The International Workshop on Reading Music Systems (WoRMS) is a workshop that tries to connect researchers who develop systems for reading music, such as in the field of Optical Music Recognition, with other researchers and practitioners that could benefit from such systems, like librarians or musicologists.

Information Retrieval Music Information Retrieval +1

Proceedings of the 4th International Workshop on Reading Music Systems

no code implementations23 Nov 2022 Jorge Calvo-Zaragoza, Alexander Pacha, Elona Shatri

The International Workshop on Reading Music Systems (WoRMS) is a workshop that tries to connect researchers who develop systems for reading music, such as in the field of Optical Music Recognition, with other researchers and practitioners that could benefit from such systems, like librarians or musicologists.

Information Retrieval Music Information Retrieval +1

DoReMi: First glance at a universal OMR dataset

1 code implementation16 Jul 2021 Elona Shatri, György Fazekas

While we do not assume to have solved the main challenges in OMR, this dataset opens a new course of discussions that would ultimately aid that goal.

object-detection Object Detection

Optical Music Recognition: State of the Art and Major Challenges

no code implementations14 Jun 2020 Elona Shatri, György Fazekas

In this paper, we review relevant works in OMR, including fundamental methods and significant outcomes, and highlight different stages of the OMR pipeline.

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