tmp-bibfile.bib

@comment{{This file has been generated by bib2bib 1.99}}
@comment{{Command line: /usr/bin/bib2bib -oc tmp-citefile -ob tmp-bibfile.bib -c '$type: "inproceedings"' pubs.bib}}
@inproceedings{JSCardosoICMLA2010,
  author = {Cardoso, Jaime S. and Sousa, Ricardo},
  booktitle = {Proceedings of The Ninth International Conference on Machine Learning and Applications (ICMLA 2010)},
  title = {{Classification Models with Global Constraints for Ordinal Data}},
  url = {http://rsousa.org/docs/pubs/JSCardosoICMLA2010.pdf},
  year = {2010}
}
@inproceedings{JaimeCCIS2009,
  author = {Cardoso, Jaime S and Sousa, Ricardo and Teixeira, Luis F and Cardoso, Maria J},
  booktitle = {Biomedical Engineering Systems and Technologies},
  editor = {Fred, A and Filipe, J and Gamboa, H},
  pages = {439--452},
  publisher = {Springer-Verlag Berlin Heidelberg},
  series = {Communications in Computer and Information Science},
  title = {{Breast Contour Detection with Stable Paths}},
  url = {http://rsousa.org/docs/pubs/JSCardosoCCIS2009.pdf},
  volume = {25},
  year = {2009}
}
@inproceedings{JFCostaICMLA2010,
  abstract = {Support vector machines (SVMs) were initially proposed to solve problems
with two classes. Despite the myriad of schemes for multiclassification
with SVMs proposed since then, little work has been done for the
case where the classes are ordered. Usually one constructs a nominal
classifier and a posteriori defines the order. The definition of
an ordinal classifier leads to a better generalisation. Moreover,
most of the techniques presented so far in the literature can generate
ambiguous regions. All-at-Once methods have been proposed to solve
this issue. In this work we devise a new SVM methodology based on
the unimodal paradigm with the All-at-Once scheme for the ordinal
classification.},
  author = {da Costa, Joaquim Pinto and Sousa, Ricardo and Cardoso, Jaime S},
  booktitle = {Proceedings of The Ninth International Conference on Machine Learning and Applications (ICMLA 2010)},
  title = {{An all-at-once Unimodal SVM Approach for Ordinal Classification}},
  url = {http://rsousa.org/docs/pubs/JFCostaICMLA2010.pdf},
  year = {2010}
}
@inproceedings{ARRNetoIBPRIA2011,
  author = {Ajalmar R. da Rocha Neto and Ricardo Sousa and Guilherme A. Barreto and Jaime S. Cardoso},
  booktitle = {Proceedings of Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)},
  title = {{Diagnostic of Pathology on the Vertebral Column with Embedded Reject Option}},
  url = {http://rsousa.org/docs/pubs/ANetoIBPRIA2011.pdf},
  year = {2011}
}
@inproceedings{Rebelo2011,
  abstract = {Although Optical Music Recognition (OMR) has been the focus of much research for decades, the processing of handwritten musical scores is not yet satisfactory. The efforts made to find robust symbol representations and learning methodologies have not found a similar quality in the learning of the dissimilarity concept. Simple Euclidean distances are often used to measure dissimilarity between different examples. However, such distances do not necessarily yield the best performance. In this paper, we propose to learn the best distance for the \~-NN) classifier. The distance concept will be tuned both for the application domain and the adopted representation for the music symbols. The performance of the method is compared with the support vector machine (SVM) classifier using both real and synthetic music scores. The synthetic database includes four types of deformations inducing variability in the printed musical symbols which exist in handwritten music sheets. The work presented here can open new research paths towards a novel automatic musical symbols recognition module for handwritten scores.},
  author = {Rebelo, Ana and Tkaczuk, Jakub and Sousa, Ricardo and Cardoso, Jaime S.},
  booktitle = {The tenth International Conference on Machine Learning and Applications (ICMLA'11)},
  keywords = {machine learning,metric learning,omr},
  mendeley-tags = {machine learning},
  title = {{Metric Learning for Music Symbol Recognition}},
  year = {2011},
  url = {http://rsousa.org/docs/pubs/ARebeloICMLA2011.pdf}
}
@inproceedings{SousaISDA2011,
  abstract = {While ordinal classification problems are common in many situations, induction of ordinal decision trees has not evolved significantly. Conventional trees for regression settings or nominal classification are commonly induced for ordinal classification problems. On the other hand a decision tree consistent with the ordinal setting is often desirable to aid decision making in such situations as credit rating. In this work we extend a recently proposed strategy based on constraints defined globally over the feature space. We propose a bootstrap technique to improve the accuracy of the baseline solution. Experiments in synthetic and real data show the benefits of our proposal.},
  address = {Cordoba, Spain, Spain},
  author = {Sousa, Ricardo and Cardoso, Jaime S},
  booktitle = {11th International Conference on Intelligent Systems Design and Applications (ISDA 2011)},
  keywords = {Classification,Decision Trees,Ensemble Learning,Ordinal Data,Supervised Learning},
  title = {{Ensemble of Decision Trees with Global Constraints for Ordinal Classification}},
  year = {2011},
  url = {http://rsousa.org/docs/pubs/RSousaISDA2011.pdf}
}
@inproceedings{RSousaICIP2008,
  author = {Sousa, Ricardo and Cardoso, Jaime S and da Costa, Joaquim F Pinto and Cardoso, Maria J},
  booktitle = {2008 15th IEEE International Conference on Image Processing, Vols 1-5},
  pages = {1440--1443},
  series = {IEEE International Conference on Image Processing (ICIP)},
  title = {{Breast Contour Detection with Shape Priors}},
  url = {http://rsousa.org/docs/pubs/RSousaICIP2008.pdf},
  year = {2008}
}
@inproceedings{RSousaICMLA2009,
  author = {Sousa, Ricardo and Mora, Beatriz and Cardoso, Jaime S},
  booktitle = {Proceedings of The Eighth International Conference on Machine Learning and Applications (ICMLA 2009)},
  keywords = {machine learning,reject option},
  title = {{An Ordinal Data Method for the Classification with Reject Option}},
  url = {http://rsousa.org/docs/pubs/RSousaICMLA2009.pdf},
  year = {2009}
}
@inproceedings{RSousaIBPRIA2011,
  author = {Sousa, Ricardo and Oliveira, H\'{e}lder P and Cardoso, Jaime S},
  booktitle = {Proceedings of The Fifth edition of the Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2011)},
  editor = {Vitri\`{a}, Jordi and Sanches, Jo\~{a}o and Hern\'{a}ndez, Mario},
  pages = {524--531},
  publisher = {Springer Berlin / Heidelberg},
  title = {{Feature Selection with Complexity Measure in a Quadratic Programming Setting}},
  url = {http://rsousa.org/docs/pubs/RSousaIBPRIA2011.pdf},
  year = {2011}
}
@inproceedings{JSCardosoICMLA2012,
  author = {Cardoso, Jaime S and Sousa, Ricardo and Domingues, Inês},
  booktitle = {Proceedings of The Tenth International Conference on Machine Learning and Applications (ICMLA 2012)},
  title = {{Ordinal Data Classification Using Kernel Discriminant Analysis: A Comparison of Three Approaches}},
  year = {2012},
  url = {http://rsousa.org/docs/pubs/JSCardosoICMLA2012.pdf}
}
@inproceedings{FMagalhaesICIAR2013,
  author = {Filipe Magalhaes and Ricardo Sousa and Francisco M. Araújo and Miguel V. Correia},
  booktitle = {Image Analysis and Recognition},
  volume = {7950},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer Berlin Heidelberg},
  pages = {758-765},
  title = {Compressive Sensing based Face Detection without Explicit Image Reconstruction using Support Vector Machines},
  year = {2013},
  url = {http://rsousa.org/docs/pubs/FMagalhaesICIAR2013.pdf}
}
@inproceedings{RSousaCBMS2013,
  author = {Ricardo Sousa and Miguel Taveres Coimbra and Mario-Dinis Ribeiro and Pedro Pimentel-Nunes},
  title = {{Impact of SVM Multiclass Decomposition Rules for Recognition of Cancer in Gastroenterology Images}},
  booktitle = {Computer-Based Medical Systems (CBMS), 2013 IEEE 26th International Symposium on},
  year = {2013},
  year = {2013},
  month = {June},
  pages = {405-408}
}
@inproceedings{RSousaESANN014,
  author = {Ricardo Sousa and Ajalmar R. da Rocha Neto and Guilherme A. Barreto and Jaime S. Cardoso and Miguel Taveres Coimbra },
  title = {{Reject Option Paradigm for the Reduction of Support Vectors}},
  booktitle = {ESANN},
  year = {2014},
  url = {http://rsousa.org/docs/pubs/RSousaESANN2014.pdf}
}
@inproceedings{RSousaICANN2014,
  author = {Ricardo Sousa and Ajalmar R. da Rocha Neto and Guilherme A. Barreto and Jaime S. Cardoso},
  title = {Classification with Reject Option Using the Self-Organizing Map},
  booktitle = {ICANN},
  year = 2014,
  url = {http://rsousa.org/docs/pubs/RSousaICANN2014.pdf}
}
@inproceedings{RSousaEMBC2014,
  author = {Ricardo Sousa and Daniel C. Moura and Mario Dinis-Ribeiro and Miguel T. Coimbra},
  title = {Local Self Similar Descriptors: Comparison and Application to Gastroenterology Images},
  booktitle = {EMBC},
  year = 2014,
  url = {http://rsousa.org/docs/pubs/RSousaEMBC2014.pdf}
}
@inproceedings{Chetak2014,
  title = {Improving Transfer Learning Accuracy by Reusing Stacked Denoising Autoencoders},
  author = {Chetak Kandaswamy and Luis M. Silva and L. M. Alexandre and Ricardo Sousa and Jorge Santos and Joaquim Marques de Sá},
  booktitle = {Proceedings of the IEEE SMC Conference},
  year = {2014},
  url = {http://rsousa.org/docs/pubs/ChetakSMC2014.pdf}
}
@inproceedings{RGamelasSousaIWANN2015,
  author = {Ricardo {Gamelas Sousa} and Tiago Esteves and Sara Rocha and Francisco Figueiredo and Joaquim M. de Sá and Luís A. Alexandre and Jorge M. Santos and Luis M. Silva},
  title = {{Transfer Learning for the Recognition of Immunogold Particles in TEM imaging}},
  year = {2015},
  booktitle = {IWANN},
  url = {http://rsousa.org/docs/pubs/RGamelasSousaIWANN2015.pdf}
}
@inproceedings{RGamelasSousaICIAR2015,
  author = {Ricardo {Gamelas Sousa} and Tiago Esteves and Sara Rocha and Francisco Figueiredo and Pedro Quelhas and Luis M. Silva},
  title = {{Automatic Detection of Immunogold Particles from Electron Microscopy Images}},
  year = {2015},
  booktitle = {ICIAR},
  url = {http://rsousa.org/docs/pubs/RGamelasSousaICIAR2015.pdf}
}
@inproceedings{BeatrizQuintinoFerreiraUnifiedModelStructuredKDD2018,
  author = {Beatriz {Quitino Ferreira} and Luís Baía and João Faria and Ricardo {Gamelas Sousa} },
  title = {{A Unified Model with Structured Output for Fashion Images Classification}},
  year = {2018},
  booktitle = {KDD},
  url = {http://rsousa.org/docs/pubs/BeatrizQuintinoFerreiraUnifiedModelStructuredKDD2018.pdf}
}
@inproceedings{JMarcelinoHierarchicalDeepLearningKDD2018,
  author = {José Marcelino and João Faria and Luís Baía and Ricardo {Gamelas Sousa} },
  title = {{A Hierarchical Deep Learning Natural Language Parser for Fashion}},
  year = {2018},
  booktitle = {KDD},
  url = {http://rsousa.org/docs/pubs/JMarcelinoHierarchicalDeepLearningKDD2018.pdf}
}