OMR-Research

[AlfaroContreras2023]	María Alfaro-Contreras. Few-Shot Music Symbol Classification via Self-Supervised Learning and Nearest Neighbor. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 39-43, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Castellanos2023]	Francisco J. Castellanos, Antonio Javier Gallego, and Ichiro Fujinaga. A Preliminary Study of Few-shot Learning for Layout Analysis of Music Scores. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 44-48, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Fujinaga2023]	Ichiro Fujinaga and Gabriel Vigliensoni. Optical Music Recognition Workflow for Medieval Music Manuscripts. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 4-6, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Hajic2023]	Jan jr. Hajič, Petr Žabička, Jan Rychtář, Jiří Mayer, Martina Dvořáková, Filip Jebavý, Markéta Vlková, and Pavel Pecina. The OmniOMR Project. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 12-14, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Hande2023]	Pranjali Hande, Elona Shatri, Benjamin Timms, and György Fazekas. Towards Artificially Generated Handwritten Sheet Music Datasets. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 25-30, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Havelka2023]	Jonáš Havelka, Jiří Mayer, and Pavel Pecina. Symbol Generation via Autoencoders for Handwritten Music Synthesis. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 20-24, Milan, Italy, 2023. [ bib \| DOI \| http ]
[MartinezSevilla2023]	Juan Carlos Martinez-Sevilla and Francisco J. Castellanos. Towards Music Notation and Lyrics Alignment: Gregorian Chants as Case Study. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 15-19, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Repolusk2023]	Tristan Repolusk and Eduardo Veas. The Suzipu Musical Annotation Tool for the Creation of Machine-Readable Datasets of Ancient Chinese Music. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 7-11, Milan, Italy, 2023. [ bib \| DOI \| http ]
[RiosVila2023]	Antonio Ríos-Vila. Rotations Are All You Need: A Generic Method For End-To-End Optical Music Recognition. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 34-38, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Zhang2023]	Zihui Zhang, Elona Shatri, and György Fazekas. Improving Sheet Music Recognition using Data Augmentation and Image Enhancement. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 5th International Workshop on Reading Music Systems, pages 31-33, Milan, Italy, 2023. [ bib \| DOI \| http ]
[Egozy2022]	Eran Egozy and Ian Clester. Computer-Assisted Measure Detection in a Music Score-Following Application. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 33-36, Online, 2022. [ bib \| DOI \| http ]
[GarridoMunoz2022]	Carlos Garrido-Munoz, Antonio Ríos-Vila, and Jorge Calvo-Zaragoza. End-to-End Graph Prediction for Optical Music Recognition. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 25-28, Online, 2022. [ bib \| DOI \| http ]
[Jacquemard2022]	Florent Jacquemard, Lydia Rodriguez-de la Nava, and Martin Digard. Automated Transcription of Electronic Drumkits. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 37-41, Online, 2022. [ bib \| DOI \| http ]
[Mayer2022]	Jiří Mayer and Pavel Pecina. Obstacles with Synthesizing Training Data for OMR. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 15-19, Online, 2022. [ bib \| DOI \| http ]
[Moss2022]	Fabian C. Moss, Néstor Nápoles López, Maik Köster, and David Rizo. Challenging sources: a new dataset for OMR of diverse 19th-century music theory examples. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 4-8, Online, 2022. [ bib \| DOI \| http ]
[Penarrubia2022]	Carlos Penarrubia, Carlos Garrido-Muñoz, Jose J. Valero-Mas, and Jorge Calvo-Zaragoza. Efficient Approaches for Notation Assembly in Optical Music Recognition. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 29-32, Online, 2022. [ bib \| DOI \| http ]
[RiosVila2022]	Antonio Ríos-Vila, Jose M. Iñesta, and Jorge Calvo-Zaragoza. End-To-End Full-Page Optical Music Recognition of Monophonic Documents via Score Unfolding. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 20-24, Online, 2022. [ bib \| DOI \| http ]
[Torras2022]	Pau Torras, Arnau Baró, Lei Kang, and Alicia Fornés. Improving Handwritten Music Recognition through Language Model Integration. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, Online, 2022. [ bib \| DOI \| http ]
[Walwadkar2022]	Dnyanesh Walwadkar, Elona Shatri, Benjamin Timms, and György Fazekas. CompIdNet: Sheet Music Composer Identification using Deep Neural Network. In Jorge Calvo-Zaragoza, Alexander Pacha, and Elona Shatri, editors, Proceedings of the 4th International Workshop on Reading Music Systems, pages 9-14, Online, 2022. [ bib \| DOI \| http ]
[AlfaroContreras2021]	María Alfaro-Contreras, Jose J. Valero-Mas, and José Manuel Iñesta. Neural architectures for exploiting the components of Agnostic Notation in Optical Music Recognition. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 33-37, Alicante, Spain, 2021. [ bib \| http ]
[Baro2021]	Arnau Baró, Carles Badal, Pau Torras, and Alicia Fornés. Handwritten Historical Music Recognition through Sequence-to-Sequence with Attention Mechanism. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 55-59, Alicante, Spain, 2021. [ bib \| http ]
[Castellanos2021]	Francisco J. Castellanos and Antonio-Javier Gallego. Unsupervised Neural Document Analysis for Music Score Images. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 50-54, Alicante, Spain, 2021. [ bib \| http ]
[Fuente2021]	Carlos de la Fuente, Jose J. Valero-Mas, Francisco J. Castellanos, and Jorge Calvo-Zaragoza. Multimodal Audio and Image Music Transcription. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 18-22, Alicante, Spain, 2021. [ bib \| http ]
[Kletz2021]	Marc Kletz and Alexander Pacha. Detecting Staves and Measures in Music Scores with Deep Learning. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 8-12, Alicante, Spain, 2021. [ bib \| http ]
[MasCandela2021]	Enrique Mas-Candela and María Alfaro-Contreras. Sequential Next-Symbol Prediction for Optical Music Recognition. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 13-17, Alicante, Spain, 2021. [ bib \| http ]
[Pacha2021]	Alexander Pacha. The Challenge of Reconstructing Digits in Music Scores. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 4-7, Alicante, Spain, 2021. [ bib \| http ]
[RiosVila2021]	Antonio Ríos-Vila, David Rizo, Jorge Calvo-Zaragoza, and José Manuel Iñesta. Completing Optical Music Recognition with Agnostic Transcription and Machine Translation. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 28-32, Alicante, Spain, 2021. [ bib \| http ]
[Samiotis2021]	Ioannis Petros Samiotis, Christoph Lofi, and Alessandro Bozzon. Hybrid Annotation Systems for Music Transcription. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 23-27, Alicante, Spain, 2021. [ bib \| http ]
[Shatri2021]	Elona Shatri and György Fazekas. DoReMi: First glance at a universal OMR dataset. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 43-49, Alicante, Spain, 2021. [ bib \| http ]
[Wenzlitschke2021]	Nils Wenzlitschke. Implementation and evaluation of a neural network for the recognition of handwritten melodies. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, Proceedings of the 3rd International Workshop on Reading Music Systems, pages 38-42, Alicante, Spain, 2021. [ bib \| http ]
[AlfaroContreras2020]	María Alfaro-Contreras, Jorge Calvo-Zaragoza, and José M. Iñesta. Reconocimiento holístico de partituras musicales. Technical report, Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Spain, 2020. [ bib \| .pdf ]
[Calvo-Zaragoza2020]	Jorge Calvo-Zaragoza, Jan Hajič Jr., and Alexander Pacha. Understanding Optical Music Recognition. ACM Comput. Surv., 53 (4), 2020. ISSN 0360-0300. [ bib \| DOI \| http ]
[Castellanos2020]	Francisco J. Castellanos, Antonio-Javier Gallego, and Jorge Calvo-Zaragoza. Automatic scale estimation for music score images. Expert Systems with Applications, page 113590, 2020. ISSN 0957-4174. [ bib \| DOI \| http ]
[Elezi2020]	Ismail Elezi. Exploiting Contextual Information with Deep Neural Networks. mathesis, Ca' Foscari, University of Venice, 2020. [ bib \| .pdf ]
[Henkel2020]	Florian Henkel, Rainer Kelz, and Gerhard Widmer. Learning to Read and Follow Music in Complete Score Sheet Images. In Proceedings of the 21st Int. Society for Music Information Retrieval Conf., 2020. [ bib \| .html ]
[Mico2020]	Luisa Micó, Jose Oncina, and José M. Iñesta. Adaptively Learning to Recognize Symbols in Handwritten Early Music. In Peggy Cellier and Kurt Driessens, editors, Machine Learning and Knowledge Discovery in Databases, pages 470-477, Cham, 2020. Springer International Publishing. ISBN 978-3-030-43887-6. [ bib \| DOI ]
[MuNG]	Alexander Pacha and Jan Hajič jr. The Music Notation Graph (MuNG) Repository. https://github.com/OMR-Research/mung, 2020. [ bib \| http ]
[Tardon2020]	Lorenzo J. Tardón, Isabel Barbancho, Ana M. Barbancho, and Ichiro Fujinaga. Automatic Staff Reconstruction within SIMSSA Project. Applied Sciences, 10 (7): 2468-2484, 2020. [ bib \| DOI \| http ]
[Tsai2020]	Timothy J. Tsai, Daniel Yang, Mengyi Shan, Thitaree Tanprasert, and Teerapat Jenrungrot. Using Cell Phone Pictures of Sheet Music To Retrieve MIDI Passages. IEEE Transactions on Multimedia, pages 1-13, 2020. [ bib \| DOI \| http ]
[Tuggener2020]	Lukas Tuggener, Yvan Putra Satyawan, Alexander Pacha, Jürgen Schmidhuber, and Thilo Stadelmann. The DeepScoresV2 Dataset and Benchmark for Music Object Detection. In Proceedings of the 25th International Conference on Pattern Recognition, Milan, Italy, 2020. [ bib \| DOI ]
[Wick2020]	Christoph Wick and Frank Puppe. Automatic Neume Transcription of Medieval Music Manuscripts using CNN/LSTM-Networks and the segmentation-free CTC-Algorithm. Technical report, University of Würzburg, 2020. [ bib \| DOI ]
[Miro2019]	Jordi Burgués Miró. Recognition of musical symbols in scores using neural networks. Master's thesis, Universitat Politècnica de Catalunya, Barcelona, June 2019. [ bib \| http ]
[Wick2019]	Christoph Wick, Alexander Hartelt, and Frank Puppe. Staff, Symbol, and Melody Detection of Medieval Manuscripts Written in Square Notation Using Deep Fully Convolutional Networks. May 2019a. [ bib \| DOI \| http ]
[Baro2019]	Arnau Baró, Pau Riba, Jorge Calvo-Zaragoza, and Alicia Fornés. From Optical Music Recognition to Handwritten Music Recognition: A baseline. Pattern Recognition Letters, 123: 1-8, 2019. ISSN 0167-8655. [ bib \| DOI \| http ]
[Calvo-Zaragoza2019]	Jorge Calvo-Zaragoza, Alejandro H. Toselli, and Enrique Vidal. Hybrid hidden Markov models and artificial neural networks for handwritten music recognition in mensural notation. Pattern Analysis and Applications, Mar 2019b. ISSN 1433-755X. [ bib \| DOI ]
[Calvo-Zaragoza2019a]	Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha. Understanding Optical Music Recognition. Computing Research Repository, 2019a. [ bib \| http ]
[Calvo-Zaragoza2019b]	Jorge Calvo-Zaragoza, Alejandro H. Toselli, and Enrique Vidal. Handwritten Music Recognition for Mensural notation with convolutional recurrent neural networks. Pattern Recognition Letters, 128: 115-121, 2019c. ISSN 0167-8655. [ bib \| DOI \| http ]
[Colesnicov2019]	Alexandru Colesnicov, Svetlana Cojocaru, Mihaela Luca, and Ludmila Malahov. On Digitization of Documents with Script Presentable Content. In Proceedings of the Fifth Conference of Mathematical Society of Moldova, 2019. [ bib \| .pdf ]
[Eipert2019]	Tim Eipert, Felix Herrman, Christoph Wick, Frank Puppe, and Andreas Haug. Editor Support for Digital Editions of Medieval Monophonic Music. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, 2nd International Workshop on Reading Music Systems, pages 4-7, Delft, The Netherlands, 2019. [ bib \| http ]
[Goularas2019]	Dionysis Goularas and Kürsat Çinar. Optical Music Recognition of the Hamparsum Notation. In 2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA), pages 1-7, Nov 2019. [ bib \| DOI ]
[Gover2019]	Matan Gover and Ichiro Fujinaga. A Notation-Based Query Language for Searching in Symbolic Music. In 6th International Conference on Digital Libraries for Musicology, DLfM ’19, pages 79-83, New York, NY, USA, 2019. Association for Computing Machinery. ISBN 9781450372398. [ bib \| DOI \| http ]
[Hajicjr.2019]	Jan Hajič jr. Optical Recognition of Handwritten Music Notation. phdthesis, Charles University, Prague, 2019. [ bib ]
[Hakim2019]	Dzikry Maulana Hakim and Ednawati Rainarli. Convolutional Neural Network untuk Pengenalan Citra Notasi Musik. Techno.COM, 18 (3): 214-226, 2019. ISSN 2356-2579. [ bib \| DOI \| http ]
[Henkel2019]	Florian Henkel, Rainer Kelz, and Gerhard Widmer. Audio-Conditioned U-Net for Position Estimation in Full Sheet Images. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, 2nd International Workshop on Reading Music Systems, pages 8-11, Delft, The Netherlands, 2019. [ bib \| http ]
[Huang2019]	Zhiquing Huang, Xiang Jia, and Yifan Guo. State-of-the-Art Model for Music Object Recognition with Deep Learning. Applied Sciences, 9 (13): 2645-2665, 2019. ISSN 2076-3417. [ bib \| DOI \| http ]
[Inesta2019]	José M. Iñesta, David Rizo, and Jorge Calvo-Zaragoza. MuRET as a software for the transcription of historical archives. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, 2nd International Workshop on Reading Music Systems, pages 12-15, Delft, The Netherlands, 2019. [ bib \| http ]
[Ju2019]	Qinjie Ju, René Chalon, and Stéphane Derrode. Assisted Music Score Reading Using Fixed-Gaze Head Movement: Empirical Experiment and Design Implications. Proc. ACM Hum.-Comput. Interact., 3 (EICS): 3:1-3:29, 2019. ISSN 2573-0142. [ bib \| DOI \| http ]
[Mateiu2019]	Tudor Nicolae Mateiu. Unsupervised Learning for Domain Adaptation in automatic classification tasks through Neural Networks. mathesis, Universidad de Alicante, 2019. [ bib \| http ]
[Mateiu2019a]	Tudor N. Mateiu, Antonio-Javier Gallego, and Jorge Calvo-Zaragoza. Domain Adaptation for Handwritten Symbol Recognition: A Case of Study in Old Music Manuscripts. In Aythami Morales, Julian Fierrez, José Salvador Sánchez, and Bernardete Ribeiro, editors, Pattern Recognition and Image Analysis, pages 135-146, Cham, 2019. Springer International Publishing. ISBN 978-3-030-31321-0. [ bib \| DOI ]
[Mengarelli2019]	Luciano Mengarelli, Bruno Kostiuk, João G. Vitório, Maicon A. Tibola, William Wolff, and Carlos N. Silla. OMR metrics and evaluation: a systematic review. Multimedia Tools and Applications, Dec 2019. ISSN 1573-7721. [ bib \| DOI ]
[Metaj2019]	Stiven Metaj and Federico Magnolfi. MNR: MUSCIMA Notes Recognition. Using Faster R-CNN on handwritten music dataset. resreport, Politecnico di Milano, 2019. [ bib \| DOI ]
[Noll2019]	Justus Noll. Intelligentes Notenlesen. c't, 18: 122-126, 2019. [ bib \| http ]
[NunezAlcover2019]	Alicia Núñez Alcover. Glyph and Position Classification of Music Symbols in Early Manuscripts. mathesis, Universidad de Alicante, 2019. [ bib \| http ]
[Nunez-Alcover2019]	Alicia Nuñez-Alcover, Pedro J. Ponce de León, and Jorge Calvo-Zaragoza. Glyph and Position Classification of Music Symbols in Early Music Manuscripts. In Aythami Morales, Julian Fierrez, José Salvador Sánchez, and Bernardete Ribeiro, editors, Pattern Recognition and Image Analysis, pages 159-168, Cham, 2019. Springer International Publishing. ISBN 978-3-030-31321-0. [ bib \| DOI ]
[OmrBibliography]	Alexander Pacha. The definitive bibliography for research on Optical Music Recognition. https://omr-research.github.io, 2019a. [ bib \| http ]
[Pacha2019]	Alexander Pacha. Self-Learning Optical Music Recognition. phdthesis, TU Wien, 2019b. [ bib \| .pdf ]
[Pacha2019a]	Alexander Pacha, Jorge Calvo-Zaragoza, and Jan Hajič jr. Learning Notation Graph Construction for Full-Pipeline Optical Music Recognition. In 20th International Society for Music Information Retrieval Conference, pages 75-82, 2019. [ bib \| .pdf ]
[Pacha2019b]	Alexander Pacha. Incremental Supervised Staff Detection. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, 2nd International Workshop on Reading Music Systems, pages 16-20, Delft, The Netherlands, 2019c. [ bib \| http ]
[Panadero2019]	Ivan Santos Panadero. Alignment of handwritten music scores. Technical report, Universitat Autónoma de Barcelona, 2019. [ bib \| .pdf ]
[Parada-Cabaleiro2019]	Emilia Parada-Cabaleiro, Anton Batliner, and Björn Schuller. A Diplomatic Edition of Il Lauro Secco: Ground Truth for OMR of White Mensural Notation. In 20th International Society for Music Information Retrieval Conference, pages 557-564, Delft, The Netherlands, 2019. [ bib \| .pdf ]
[Regimbal2019]	Juliette Regimbal, McLennan Zoé, Gabriel Vigliensoni, Andrew Tran, and Ichiro Fujinaga. Neon2: A Verovio-based square-notation editor. In Music Encoding Conference 2019, Vienna, Austria, 2019. [ bib \| .pdf ]
[Reuse2019]	Timothy de Reuse and Ichiro Fujinaga. Robust Transcript Alignment on Medieval Chant Manuscripts. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, 2nd International Workshop on Reading Music Systems, pages 21-26, Delft, The Netherlands, 2019. [ bib \| http ]
[Rios-Vila2019]	Antonio Ríos-Vila, Jorge Calvo-Zaragoza, David Rizo, and José M. Iñesta. ReadSco: An Open-Source Web-Based Optical Music Recognition Tool. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, 2nd International Workshop on Reading Music Systems, pages 27-30, Delft, The Netherlands, 2019. [ bib \| http ]
[Thomae2019]	Martha E. Thomae, Julie E. Cumming, and Ichiro Fujinaga. The Mensural Scoring-up Tool. In 6th International Conference on Digital Libraries for Musicology, DLfM ’19, pages 9-19, New York, NY, USA, 2019. Association for Computing Machinery. ISBN 9781450372398. [ bib \| DOI \| http ]
[Vigliensoni2019]	Gabriel Vigliensoni, Alex Daigle, Eric Liu, Jorge Calvo-Zaragoza, Juliette Regimbal, Minh Anh Nguyen, Noah Baxter, Zoé McLennan, and Ichiro Fujinaga. From image to encoding: Full optical music recognition of Medieval and Renaissance music. In Music Encoding Conference, 2019. [ bib \| .pdf ]
[Waloschek2019]	Simon Waloschek, Aristotelis Hadjakos, and Alexander Pacha. Identification and Cross-Document Alignment of Measures in Music Score Images. In 20th International Society for Music Information Retrieval Conference, pages 137-143, 2019. [ bib \| .pdf ]
[Wick2019a]	Christoph Wick, Alexander Hartelt, and Frank Puppe. Staff, Symbol and Melody Detection of Medieval Manuscripts Written in Square Notation Using Deel Fully Convolutional Networks. Applied Sciences, 9 (13): 2646-2673, 2019b. ISSN 2076-3417. [ bib \| DOI \| http ]
[Wick2019b]	Christoph Wick and Frank Puppe. OMMR4all - a Semiautomatic Online Editor for Medieval Music Notations. In Jorge Calvo-Zaragoza and Alexander Pacha, editors, 2nd International Workshop on Reading Music Systems, pages 31-34, Delft, The Netherlands, 2019. [ bib \| http ]
[Xiao2019]	Zhe Xiao, Xin Chen, and Li Zhou. Real-Time Optical Music Recognition System for Dulcimer Musical Robot. Journal of Advanced Computational Intelligence and Intelligent Informatics, 23 (4): 782-790, 2019. [ bib \| DOI ]
[Zalkow2019]	Frank Zalkow, Angel Villar Corrales, TJ Tsai, Vlora Arifi-Müller, and Meinard Müller. Tools For Semi-Automatic Bounding Box Annotation Of Musical Measures In Sheet Music. In Late Breaking/Demo at 20th International Society for Music Information Retrieval, Delft, The Netherlands, 2019. [ bib ]
[Achankunju2018]	Sanu Pulimootil Achankunju. Music Search Engine from Noisy OMR Data. In Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha, editors, 1st International Workshop on Reading Music Systems, pages 23-24, Paris, France, 2018. [ bib \| http ]
[Balke2018]	Stefan Balke, Christian Dittmar, Jakob Abeßer, Klaus Frieler, Martin Pfleiderer, and Meinard Müller. Bridging the Gap: Enriching YouTube Videos with Jazz Music Annotations. Frontiers in Digital Humanities, 5: 1-11, 2018. ISSN 2297-2668. [ bib \| DOI ]
[Baro2018]	Arnau Baró, Pau Riba, and Alicia Fornés. A Starting Point for Handwritten Music Recognition. In Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha, editors, 1st International Workshop on Reading Music Systems, pages 5-6, Paris, France, 2018. [ bib \| http ]
[Bonnici2018]	Alexandra Bonnici, Julian Abela, Nicholas Zammit, and George Azzopardi. Automatic Ornament Localisation, Recognition and Expression from Music Sheets. In ACM Symposium on Document Engineering, pages 25:1-25:11, Halifax, NS, Canada, 2018. ACM. ISBN 978-1-4503-5769-2. [ bib \| DOI \| http ]
[Calvo-Zaragoza2018]	Jorge Calvo-Zaragoza and David Rizo. End-to-End Neural Optical Music Recognition of Monophonic Scores. Applied Sciences, 8 (4), 2018a. ISSN 2076-3417. [ bib \| DOI \| http ]
[Calvo-Zaragoza2018a]	Jorge Calvo-Zaragoza, Francisco J. Castellanos, Gabriel Vigliensoni, and Ichiro Fujinaga. Deep Neural Networks for Document Processing of Music Score Images. Applied Sciences, 8 (5), 2018a. ISSN 2076-3417. [ bib \| DOI \| http ]
[Calvo-Zaragoza2018b]	Jorge Calvo-Zaragoza and David Rizo. Camera-PrIMuS: Neural End-to-End Optical Music Recognition on Realistic Monophonic Scores. In 19th International Society for Music Information Retrieval Conference, pages 248-255, Paris, France, 2018b. ISBN 978-2-9540351-2-3. [ bib \| .pdf ]
[Calvo-Zaragoza2018c]	Jorge Calvo-Zaragoza. Why WoRMS? In Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha, editors, 1st International Workshop on Reading Music Systems, pages 7-8, Paris, France, 2018. [ bib \| http ]
[Calvo-Zaragoza2018d]	Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha. Discussion Group Summary: Optical Music Recognition. In Alicia Fornés and Lamiroy Bart, editors, Graphics Recognition, Current Trends and Evolutions, Lecture Notes in Computer Science, pages 152-157. Springer International Publishing, 2018b. ISBN 978-3-030-02283-9. [ bib \| DOI ]
[Calvo-Zaragoza2018e]	Jorge Calvo-Zaragoza, Alejandro H. Toselli, and Enrique Vidal. Probabilistic Music-Symbol Spotting in Handwritten Scores. In 16th International Conference on Frontiers in Handwriting Recognition, pages 558-563, Niagara Falls, USA, 2018d. [ bib \| DOI ]
[Castellanos2018]	Fancisco J. Castellanos, Jorge Calvo-Zaragoza, Gabriel Vigliensoni, and Ichiro Fujinaga. Document Analysis of Music Score Images with Selectional Auto-Encoders. In 19th International Society for Music Information Retrieval Conference, pages 256-263, Paris, France, 2018. ISBN 978-2-9540351-2-3. [ bib \| .pdf ]
[Chen2018]	Liang Chen and Christopher Raphael. Optical Music Recognition and Human-in-the-loop Computation. In Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha, editors, 1st International Workshop on Reading Music Systems, pages 11-12, Paris, France, 2018. [ bib \| http ]
[Choi2018]	Kwon-Young Choi, Bertrand Coüasnon, Yann Ricquebourg, and Richard Zanibbi. Music Symbol Detection with Faster R-CNN Using Synthetic Annotations. In Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha, editors, 1st International Workshop on Reading Music Systems, pages 9-10, Paris, France, 2018. [ bib \| http ]
[Crawford2018]	Tim Crawford, Golnaz Badkobeh, and David Lewis. Searching Page-Images of Early Music Scanned with OMR: A Scalable Solution Using Minimal Absent Words. In 19th International Society for Music Information Retrieval Conference, pages 233-239, Paris, France, 2018. ISBN 978-2-9540351-2-3. [ bib \| .pdf ]
[Diet2018]	Jürgen Diet. Optical Music Recognition in der Bayerischen Staatsbibliothek. BIBLIOTHEK - Forschung und Praxis, 2018a. [ bib \| DOI ]
[Diet2018a]	Jürgen Diet. Innovative MIR Applications at the Bayerische Staatsbibliothek. In 5th International Conference on Digital Libraries for Musicology, Paris, France, 2018b. [ bib \| .pdf ]
[Dorfer2018]	Matthias Dorfer, Jan Hajič jr., Andreas Arzt, Harald Frostel, and Gerhard Widmer. Learning Audio-Sheet Music Correspondences for Cross-Modal Retrieval and Piece Identification. Transactions of the International Society for Music Information Retrieval, 1 (1): 22-33, 2018a. [ bib \| DOI ]
[Dorfer2018a]	Matthias Dorfer, Florian Henkel, and Gerhard Widmer. Learning To Listen, Read And Follow: Score Following As A Reinforcement Learning Game. In 19th International Society for Music Information Retrieval Conference, pages 784-791, Paris, France, 2018b. ISBN 978-2-9540351-2-3. [ bib \| .pdf ]
[Elezi2018]	Ismail Elezi, Lukas Tuggener, Marcello Pelillo, and Thilo Stadelmann. DeepScores and Deep Watershed Detection: current state and open issues. In Jorge Calvo-Zaragoza, Jan Hajič jr., and Alexander Pacha, editors, 1st International Workshop on Reading Music Systems, pages 13-14, Paris, France, 2018. [ bib \| http ]
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Bibliography on Optical Music Recognition