| Records |
| Author |
Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin |
| Title |
Subclass Problem-Dependent Design for Error-Correcting Output Codes |
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Journal |
| Year |
2008 |
Publication |
IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(6):1041–1054 |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ ETP2008 |
Serial |
951 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Detection of Complex Salient Regions |
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Journal |
| Year |
2008 |
Publication |
EURASIP Journal on Advances in Signal Processing, vol. 2008, article ID451389, 11 pages |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2008b |
Serial |
960 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Sub-Class Error-Correcting Output Codes |
Type |
Book Chapter |
| Year |
2008 |
Publication |
Computer Vision Systems. 6th International Conference |
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| Volume |
5008 |
Issue |
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Pages |
494–504 |
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Santorini (Greece) |
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ICVS |
| Notes |
MILAB;HuPBA |
Approved |
no |
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BCNPCL @ bcnpcl @ EPR2008c |
Serial |
963 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Loss-Weighted Decoding for Error-Correcting Output Coding |
Type |
Conference Article |
| Year |
2008 |
Publication |
3rd International Conference on Computer Vision Theory and Applications, |
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| Volume |
2 |
Issue |
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Pages |
117–122 |
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| Address |
Madeira (Portugal) |
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VISAPP |
| Notes |
MILAB;HuPBA |
Approved |
no |
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BCNPCL @ bcnpcl @ EPR2008a |
Serial |
964 |
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| Author |
O. Rodriguez-Leor; Carlo Gatta; E Fernandez-Nofrerias; Oriol Pujol; Neus Salvatella; C. Bosch; H. Tizon; Petia Radeva; J. Mauri |
| Title |
Computationally Efficient Image-based IVUS Pullbacks Gating |
Type |
Journal |
| Year |
2008 |
Publication |
European Heart Journal, ESC Supplement, Munich, 2008, p. 775 |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ RGF2008 |
Serial |
1036 |
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| Author |
Carlo Gatta; Oriol Pujol; O. Rodriguez-Leor; J. Mauri; Petia Radeva |
| Title |
Robust Image-based IVUS Pullbacks Gating |
Type |
Book Chapter |
| Year |
2008 |
Publication |
Proceedings 11th International ConferenceMedical Image Computing and Computer–Assisted Intervention |
Abbreviated Journal |
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| Volume |
5242 |
Issue |
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Pages |
518–525 |
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NY (USA) |
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LNCS |
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MICCAI |
| Notes |
MILAB;HuPBA |
Approved |
no |
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BCNPCL @ bcnpcl @ GPR2008a |
Serial |
1037 |
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| Author |
Carlo Gatta; Oriol Pujol; O. Rodriguez-Leor; Josefina Mauri; Petia Radeva |
| Title |
Improved Rigid Registration of Vessel Structures using the Fast Radial Symmetry Transform |
Type |
Conference Article |
| Year |
2008 |
Publication |
Computer Vision for Intravascular Imaging CVII’08 Workshop Medical Image Computing and Computer–Assisted Intervention , 11th International Conference |
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Issue |
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Pages |
128–136 |
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| Address |
NY (USA) |
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MICCAI |
| Notes |
MILAB;HUPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ GPR2008b |
Serial |
1038 |
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| Author |
Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva |
| 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. |
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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. |
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Conference |
CVPR |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPM2008 |
Serial |
1041 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| 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 |
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| 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. |
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| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2009a |
Serial |
1153 |
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| Author |
Francesco Ciompi; Oriol Pujol; O. Rodriguez-Leor; Carlo Gatta; Angel Serrano; Petia Radeva |
| Title |
Enhancing In-Vitro IVUS Data for Tissue Characterization |
Type |
Conference Article |
| Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
5524 |
Issue |
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Pages |
241–248 |
| Keywords |
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| Abstract |
Intravascular Ultrasound (IVUS) data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue, obtaining a reliable ground truth. The main drawback of this method is the few number of available study cases due to the complex procedure of histological analysis. In this work we propose a novel semi-supervised approach to enhance the in-vitro training set by including examples from in-vivo coronary plaques data set. For this purpose, a Sequential Floating Forward Selection method is applied on in-vivo data and plaque characterization performances are evaluated by Leave-One-Patient-Out cross-validation technique. Supervised data inclusion improves global classification accuracy from 89.39% to 91.82%. |
| Address |
Póvoa de Varzim, Portugal |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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LNCS |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-02171-8 |
Medium |
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Expedition |
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Conference |
IbPRIA |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ CPR2009a |
Serial |
1162 |
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| Author |
Sergio Escalera; Eloi Puertas; Petia Radeva; Oriol Pujol |
| Title |
Multimodal laughter recognition in video conversations |
Type |
Conference Article |
| Year |
2009 |
Publication |
2nd IEEE Workshop on CVPR for Human communicative Behavior analysis |
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| Volume |
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Issue |
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Pages |
110–115 |
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| Abstract |
Laughter detection is an important area of interest in the Affective Computing and Human-computer Interaction fields. In this paper, we propose a multi-modal methodology based on the fusion of audio and visual cues to deal with the laughter recognition problem in face-to-face conversations. The audio features are extracted from the spectogram and the video features are obtained estimating the mouth movement degree and using a smile and laughter classifier. Finally, the multi-modal cues are included in a sequential classifier. Results over videos from the public discussion blog of the New York Times show that both types of features perform better when considered together by the classifier. Moreover, the sequential methodology shows to significantly outperform the results obtained by an Adaboost classifier. |
| Address |
Miami (USA) |
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Edition |
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| ISSN |
2160-7508 |
ISBN |
978-1-4244-3994-2 |
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Conference |
CVPR |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2009c |
Serial |
1188 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Recoding Error-Correcting Output Codes |
Type |
Conference Article |
| Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
Abbreviated Journal |
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| Volume |
5519 |
Issue |
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Pages |
11–21 |
| Keywords |
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| 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) |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Summary Language |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-02325-5 |
Medium |
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Expedition |
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Conference |
MCS |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2009d |
Serial |
1190 |
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| Author |
Francesco Ciompi; Oriol Pujol; O. Rodriguez-Leor; Angel Serrano; J. Mauri; Petia Radeva |
| Title |
On in-vitro and in-vivo IVUS data fusion |
Type |
Conference Article |
| Year |
2009 |
Publication |
12th International Conference of the Catalan Association for Artificial Intelligence |
Abbreviated Journal |
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| Volume |
202 |
Issue |
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Pages |
147-156 |
| Keywords |
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| Abstract |
The design and the validation of an automatic plaque characterization technique based on Intravascular Ultrasound (IVUS) usually requires a data ground-truth. The histological analysis of post-mortem coronary arteries is commonly assumed as the state-of-the-art process for the extraction of a reliable data-set of atherosclerotic plaques. Unfortunately, the amount of data provided by this technique is usually few, due to the difficulties in collecting post-mortem cases and phenomena of tissue spoiling during histological analysis. In this paper we tackle the process of fusing in-vivo and in-vitro IVUS data starting with the analysis of recently proposed approaches for the creation of an enhanced IVUS data-set; furthermore, we propose a new approach, named pLDS, based on semi-supervised learning with a data selection criterion. The enhanced data-set obtained by each one of the analyzed approaches is used to train a classifier for tissue characterization purposes. Finally, the discriminative power of each classifier is quantitatively assessed and compared by classifying a data-set of validated in-vitro IVUS data. |
| Address |
Cardona (Spain) |
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Edition |
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ISBN |
978-1-60750-061-2 |
Medium |
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| Area |
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Expedition |
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Conference |
CCIA |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ CPR2009d |
Serial |
1204 |
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| Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
| Title |
Face-to-face social activity detection using data collected with a wearable device |
Type |
Conference Article |
| Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
5524 |
Issue |
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Pages |
56–63 |
| Keywords |
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| Abstract |
In this work the feasibility of building a socially aware badge that learns from user activities is explored. A wearable multisensor device has been prototyped for collecting data about user movements and photos of the environment where the user acts. Using motion data, speaking and other activities have been classified. Images have been analysed in order to complement motion data and help for the detection of social behaviours. A face detector and an activity classifier are both used for detecting if users have a social activity in the time they worn the device. Good results encourage the improvement of the system at both hardware and software level |
| Address |
Póvoa de Varzim, Portugal |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-02171-8 |
Medium |
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Expedition |
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Conference |
IbPRIA |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ CPR2009b |
Serial |
1206 |
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| Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva |
| Title |
ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences |
Type |
Conference Article |
| Year |
2009 |
Publication |
12th International Conference on Medical Image and Computer Assisted Intervention |
Abbreviated Journal |
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| Volume |
5762 |
Issue |
II |
Pages |
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| Keywords |
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| Abstract |
The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers. |
| Address |
London, UK |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-04270-6 |
Medium |
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Expedition |
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Conference |
MICCAI |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ CPF2009 |
Serial |
1228 |
| Permanent link to this record |
