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Author (up) Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva edit  doi
openurl 
  Title IVUS Tissue Characterization with Sub-class Error-correcting Output Codes Type Conference Article
  Year 2008 Publication Computer Vision and Pattern Recognition Workshops, 2008. CVPR Workshops 2008. IEEE Computer Society Conference on, pp. 1–8, 23–28 juny 2008. Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on Radio Frequency, texture-based, slope-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different subsets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers and feature sets.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVPR  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPM2008 Serial 1041  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva edit  doi
openurl 
  Title Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes Type Journal Article
  Year 2009 Publication Journal of Signal Processing Systems Abbreviated Journal  
  Volume 55 Issue 1-3 Pages 35–47  
  Keywords  
  Abstract Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1939-8018 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPM2009 Serial 1258  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Boosted Landmarks of Contextual Descriptors and Forest-ECOC: a novel framework to detect and classify objects in cluttered scenes Type Miscellaneous
  Year 2006 Publication 18th International Conference on Pattern Recognition (ICPR´06), 4: 104–107, ISBN: 0–7695–2521–0 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Hong Kong  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2006a Serial 692  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title ECOC-ONE: A novel coding and decoding strategy Type Miscellaneous
  Year 2006 Publication 18th International Conference on Pattern Recognition (ICPR´06), 3: 578–581, ISBN: 0–7695–2521–0 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Hong Kong  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2006b Serial 693  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Decoding of Ternary Error Correcting Output Codes Type Book Chapter
  Year 2006 Publication 11th Iberoamerican Congress on Pattern Recognition (CIARP´06), LNCS 4225: 753–763 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Cancun (Mexico)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2006e Serial 696  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Robust Complex Salient Regions Type Book Chapter
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:113–121 Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2007b Serial 906  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Boosted Landmarks of Contextual Descriptors and Forest-ECOC: a Novel Framework to Detect and Classify Objects in Cluttered Scenes Type Journal
  Year 2007 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2007c Serial 907  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Traffic Sign Classification using Error Correcting Techniques Type Conference Article
  Year 2007 Publication 2nd International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume Issue Pages 281–285  
  Keywords  
  Abstract  
  Address Barcelona (Spain)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference VISAPP  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2007a Serial 909  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Detection of Complex Salient Regions Type Journal
  Year 2008 Publication EURASIP Journal on Advances in Signal Processing, vol. 2008, article ID451389, 11 pages Abbreviated Journal  
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  Abstract  
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  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2008b Serial 960  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Sub-Class Error-Correcting Output Codes Type Book Chapter
  Year 2008 Publication Computer Vision Systems. 6th International Conference Abbreviated Journal  
  Volume 5008 Issue Pages 494–504  
  Keywords  
  Abstract  
  Address Santorini (Greece)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICVS  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2008c Serial 963  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Loss-Weighted Decoding for Error-Correcting Output Coding Type Conference Article
  Year 2008 Publication 3rd International Conference on Computer Vision Theory and Applications, Abbreviated Journal  
  Volume 2 Issue Pages 117–122  
  Keywords  
  Abstract  
  Address Madeira (Portugal)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference VISAPP  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2008a Serial 964  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title Separability of Ternary Codes for Sparse Designs of Error-Correcting Output Codes Type Journal Article
  Year 2009 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 30 Issue 3 Pages 285–297  
  Keywords  
  Abstract Error Correcting Output Codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. In this paper, we present a new formulation of the ternary ECOC distance and the error-correcting capabilities in the ternary ECOC framework. Based on the new measure, we stress on how to design coding matrices preventing codification ambiguity and propose a new Sparse Random coding matrix with ternary distance maximization. The results on the UCI Repository and in a real speed traffic categorization problem show that when the coding design satisfies the new ternary measures, significant performance improvement is obtained independently of the decoding strategy applied.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2009a Serial 1153  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  doi
isbn  openurl
  Title Recoding Error-Correcting Output Codes Type Conference Article
  Year 2009 Publication 8th International Workshop of Multiple Classifier Systems Abbreviated Journal  
  Volume 5519 Issue Pages 11–21  
  Keywords  
  Abstract One of the most widely applied techniques to deal with multi- class categorization problems is the pairwise voting procedure. Recently, this classical approach has been embedded in the Error-Correcting Output Codes framework (ECOC). This framework is based on a coding step, where a set of binary problems are learnt and coded in a matrix, and a decoding step, where a new sample is tested and classified according to a comparison with the positions of the coded matrix. In this paper, we present a novel approach to redefine without retraining, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information increases the generalization capability of the system. Moreover, the final classification can be tuned with the inclusion of a weighting matrix in the decoding step. The approach has been validated over several UCI Machine Learning repository data sets and two real multi-class problems: traffic sign and face categorization. The results show that performance improvements are obtained when comparing the new approach to one of the best ECOC designs (one-versus-one). Furthermore, the novel methodology obtains at least the same performance than the one-versus-one ECOC design.  
  Address Reykjavik (Iceland)  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02325-5 Medium  
  Area Expedition Conference MCS  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2009d Serial 1190  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title Traffic sign recognition system with β -correction Type Journal Article
  Year 2010 Publication Machine Vision and Applications Abbreviated Journal MVA  
  Volume 21 Issue 2 Pages 99–111  
  Keywords  
  Abstract Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0932-8092 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HUPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2010a Serial 1276  
Permanent link to this record
 
 
Author (up) Sergio Escalera; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title On the Decoding Process in Ternary Error-Correcting Output Codes Type Journal Article
  Year 2010 Publication IEEE on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI  
  Volume 32 Issue 1 Pages 120–134  
  Keywords  
  Abstract A common way to model multiclass classification problems is to design a set of binary classifiers and to combine them. Error-correcting output codes (ECOC) represent a successful framework to deal with these type of problems. Recent works in the ECOC framework showed significant performance improvements by means of new problem-dependent designs based on the ternary ECOC framework. The ternary framework contains a larger set of binary problems because of the use of a ldquodo not carerdquo symbol that allows us to ignore some classes by a given classifier. However, there are no proper studies that analyze the effect of the new symbol at the decoding step. In this paper, we present a taxonomy that embeds all binary and ternary ECOC decoding strategies into four groups. We show that the zero symbol introduces two kinds of biases that require redefinition of the decoding design. A new type of decoding measure is proposed, and two novel decoding strategies are defined. We evaluate the state-of-the-art coding and decoding strategies over a set of UCI machine learning repository data sets and into a real traffic sign categorization problem. The experimental results show that, following the new decoding strategies, the performance of the ECOC design is significantly improved.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0162-8828 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HUPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2010b Serial 1277  
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