| Evaluating the Genre Classification Performance of Lyrical Features Relative to Audio, Symbolic and Cultural Features. C McKay, JA Burgoyne, J Hockman, JBL Smith, G Vigliensoni, I Fujinaga ISMIR, 213-218, 2010 | 76 | 2010 |
| Deep neural networks for document processing of music score images J Calvo-Zaragoza, FJ Castellanos, G Vigliensoni, I Fujinaga Applied Sciences 8 (5), 654, 2018 | 54 | 2018 |
| Pixel-wise binarization of musical documents with convolutional neural networks J Calvo-Zaragoza, G Vigliensoni, I Fujinaga 2017 Fifteenth IAPR international conference on machine vision applications …, 2017 | 40 | 2017 |
| The music listening histories dataset. G Vigliensoni, I Fujinaga ISMIR, 96-102, 2017 | 39 | 2017 |
| Automatic Music Recommendation Systems: Do Demographic, Profiling, and Contextual Features Improve Their Performance?. G Vigliensoni, I Fujinaga ISMIR, 94-100, 2016 | 33 | 2016 |
| A Quantitative Comparison of Position Trackers for the Development of a Touch-less Musical Interface. G Vigliensoni, MM Wanderley NIME, 2012 | 32 | 2012 |
| Optical Measure Recognition in Common Music Notation. G Vigliensoni, G Burlet, I Fujinaga ISMIR, 125-130, 2013 | 25 | 2013 |
| Automatic pitch recognition in printed square-note notation G Vigliensoni, JA Burgoyne, A Hankinson, I Fujinaga Proc. ISMIR, Florida, USA, 2011 | 23 | 2011 |
| Encoding matters N Nápoles, G Vigliensoni, I Fujinaga Proceedings of the 5th International Conference on Digital Libraries for …, 2018 | 19 | 2018 |
| Document Analysis of Music Score Images with Selectional Auto-Encoders. FJ Castellanos, J Calvo-Zaragoza, G Vigliensoni, I Fujinaga ISMIR, 256-263, 2018 | 19 | 2018 |
| Digital Document Image Retrieval Using Optical Music Recognition. A Hankinson, JA Burgoyne, G Vigliensoni, A Porter, J Thompson, W Liu, ... ISMIR, 577-582, 2012 | 19 | 2012 |
| Creating a large-scale searchable digital collection from printed music materials A Hankinson, JA Burgoyne, G Vigliensoni, I Fujinaga Proceedings of the 21st International Conference on World Wide Web, 903-908, 2012 | 19 | 2012 |
| Creating latent spaces for modern music genre rhythms using minimal training data G Vigliensoni, L McCallum, R Fiebrink Goldsmiths, University of London, 2020 | 18 | 2020 |
| One-Step Detection of Background, Staff Lines, and Symbols in Medieval Music Manuscripts with Convolutional Neural Networks. J Calvo-Zaragoza, G Vigliensoni, I Fujinaga ISMIR, 724-730, 2017 | 16 | 2017 |
| A small-data mindset for generative AI creative work G Vigliensoni, P Perry, R Fiebrink | 15 | 2022 |
| Pixel. js: Web-based pixel classification correction platform for ground truth creation Z Saleh, K Zhang, J Calvo-Zaragoza, G Vigliensoni, I Fujinaga 2017 14th IAPR International Conference on Document Analysis and Recognition …, 2017 | 15 | 2017 |
| Soundcatcher: explorations in audio-looping and time-freezing using an open-air gestural controller G Vigliensoni, MM Wanderley ICMC, 2010 | 15 | 2010 |
| Neon2: A Verovio-based square-notation editor J Regimbal, Z McLennan, G Vigliensoni, A Tran, I Fujinaga Music Encoding Conference, 2019 | 12 | 2019 |
| Document analysis for music scores via machine learning J Calvo-Zaragoza, G Vigliensoni, I Fujinaga Proceedings of the 3rd International workshop on Digital Libraries for …, 2016 | 10 | 2016 |
| The effects of translation between symbolic music formats: A case study with Humdrum, Lilypond, MEI, and MusicXML NN López, G Vigliensoni, I Fujinaga Music Encoding Conference 2019, 2019 | 9 | 2019 |
Ichiro FujinagaProfessor, Music Technology Area, Schulich School of Music, McGill UniversityVerified email at mcgill.ca
