New paper accepted: María Hontanilla, Carlos Pérez-Sancho, and Jose Manuel Iñesta, “Music style recognition with language models – beyond statistical results”. In MML 2017
Antonio-Javier Gallego and Jorge Calvo-Zaragoza. “Staff-line removal with Selectional Auto-Encoders”. In: Expert Systems With Applications
Jorge Calvo-Zaragoza, Antonio-Javier Gallego, Antonio Pertusa, “Recognition of Handwritten Music Symbols with Convolutional Neural Codes”. In: 14th IAPR International Conference on Document Analysis and Recognition (ICDAR 2017)
Jorge Calvo-Zaragoza, Alejandro Toselli, Enrique Vidal, “Handwritten Music Recognition for Mensural Notation: Formulation, Data and Baseline Results”. In: 14th IAPR International Conference on Document Analysis and Recognition (ICDAR 2017)
Jorge Calvo Zaragoza has been awarded with “Accésit AERFAI a la mejor tesis doctoral 2015-2016”
New paper accepted: Jorge Calvo-Zaragoza, Jose J. Valero-Mas, Antonio Pertusa, “End-to-end Optical Music Recognition using Neural Networks”. In: ISMIR 2017
New paper accepted: Jorge Calvo-Zaragoza, Gabriel Vigliensoni, Ichiro Fujinaga “One-step detection of background, staff lines, and symbols in medieval music manuscripts with convolutional neural networks”. In: ISMIR 2017
New paper accepted: Jose J. Valero-Mas, José M. Iñesta “Interactive User Correction of Automatically Detected Onsets: Approach and Evaluation” In: EURASIP Journal on Audio, Speech, and Music Processing, 2017
New paper accepted: Jorge Calvo-Zaragoza, Antonio Pertusa, Jose Oncina “Staff-line detection and removal using a convolutional neural network” In: Machine Vision and Applications, 2017
New paper accepted: Jose J. Valero-Mas, Emmanouil Benetos, José M. Iñesta “Assessing the Relevance of Onset Information for Note Tracking in Piano Music Transcription” In: AES International Conference on Semantic Audio 2017