The PhD thesis “Pattern Recognition for Music Notation” presente…
July 4, 2016
The PhD thesis “Pattern Recognition for Music Notation” presented by Jorge Calvo Zaragoza has obtained a “Cum Laude”.
The PhD thesis “Pattern Recognition for Music Notation” presented by Jorge Calvo Zaragoza has obtained a “Cum Laude”.
New paper accepted: Aurélien Bellet, Jose F. Bernarbeu, Amaury Habrard, Marc Sebban. “Learning Discriminative Tree Edit Similarities for Linear Classification – Application to Melody Recognition”. In: Neurocomputing
Communication: David Rizo has presented the work “A MEI module proposal for hierarchical analysis” in the 4th Music Encoding Conference in Montreal, Canada.
The 9th international workshop on Machine Learning and Music (MML2016) has been accepted to be co-located together with the next ECML-PKDD 2016 in Riva de Garda (Italy), next September.
New paper accepted: Pedro J. Ponce de León, Jose M. Iñesta, Jorge Calvo-Zaragoza, David Rizo. “Data-based melody generation through multi-objective evolutionary computation”. In: Journal of Mathematics and Music.
New paper accepted: Jorge Calvo-Zaragoza, Jose J. Valero-Mas, Juan R. Rico-Juan. "Selecting promising classes from generated data for an efficient multi-class NN classification". In: Soft Computing
New paper accepted: Marisa Bernabeu, Antonio Pertusa, Antonio-Javier Gallego. "Image Spatial Verification using Segment Intersection of Interest Points". In WSCG International Conference in Central Europe on Computer Graphics, Visualization and
New paper accepted: Jorge Calvo-Zaragoza, Colin De La Higuera and Jose Oncina. "Computing the Expected Edit Distance from a String to a PFA". In: 21st International Conference on Implementation and Application of Automata (CIAA 2016)
New paper accepted: Jose J. Valero-Mas, Jorge Calvo-Zaragoza; Juan R. Rico-Juan, and Jose M. Iñesta. "An Experimental study on Rank Methods for Prototype Selection". In: Soft Computing
New paper accepted: Jorge Calvo-Zaragoza, Jose J. Valero-Mas, Juan R. Rico-Juan. "Prototype Generation on Structural Data using Dissimilarity Space Representation". In: Neural Computing and Applications (IbPRIA 2015 special issue)