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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Approximate Convex Hulls Family for One-Class Cassification |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International Workshop on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
106-115 |
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Abstract |
In this work, a new method for one-class classification based on the Convex Hull geometric structure is proposed. The new method creates a family of convex hulls able to fit the geometrical shape of the training points. The increased computational cost due to the creation of the convex hull in multiple dimensions is circumvented using random projections. This provides an approximation of the original structure with multiple bi-dimensional views. In the projection planes, a mechanism for noisy points rejection has also been elaborated and evaluated. Results show that the approach performs considerably well with respect to the state the art in one-class classification. |
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Address |
Napoli, Italy |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21556-8 |
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Conference |
MCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPR2011b |
Serial |
1761 |
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Permanent link to this record |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Human Activity Recognition from Accelerometer Data using a Wearable Device |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
289-296 |
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Abstract |
Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing. In our work, we developed a novel wearable system easy to use and comfortable to bring. Our wearable system is based on a new set of 20 computationally efficient features and the Random Forest classifier. We obtain very encouraging results with classification accuracy of human activities recognition of up to 94%. |
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Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer Berlin Heidelberg |
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Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ CPR2011a |
Serial |
1735 |
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Author |
Francesco Ciompi; A. Palaioroutas; M. Loeve; Oriol Pujol; Petia Radeva; H. Tiddens; M. de Bruijne |
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Title |
Lung Tissue Classification in Severe Advanced Cystic Fibrosis from CT Scans |
Type |
Conference Article |
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Year |
2011 |
Publication |
In MICCAI 2011 4th International Workshop on Pulmonary Image Analysis |
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Toronto, Canada |
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PIA |
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Notes |
MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ CPL2011 |
Serial |
1798 |
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Permanent link to this record |
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Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva |
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Title |
A Holistic Approach for the Detection of Media-Adventitia Border in IVUS |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
6893 |
Issue |
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Pages |
401-408 |
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Abstract |
In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm. |
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Address |
Toronto, Canada |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-23625-9 |
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Conference |
MICCAI |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPG2011 |
Serial |
1739 |
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Permanent link to this record |
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Author |
Francesco Ciompi; Oriol Pujol; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva |
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Title |
Automatic Key Frames Detection in Intravascular Ultrasound Sequences |
Type |
Conference Article |
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Year |
2011 |
Publication |
In MICCAI 2011 Workshop on Computing and Visualization for Intra Vascular Imaging |
Abbreviated Journal |
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Abstract |
We present a method for the automatic detection of key frames in Intravascular Ultrasound (IVUS) sequences. The key frames are markers delimiting morphological changes along the vessel. The aim of defining key frames is two-fold: (1) they allow to summarize the content of the pullback into few representative frames; (2) they represent the basis for the automatic detection of clinical events in IVUS. The proposed approach achieved a compression ratio of 0.016 with respect to the original sequence and an average inter-frame distance of 61.76 frame, minimizing the number of missed clinical events. |
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Conference |
CVII |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPB2011 |
Serial |
1767 |
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Permanent link to this record |
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Author |
Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez; Xavier Roca |
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Title |
A Selective Spatio-Temporal Interest Point Detector for Human Action Recognition in Complex Scenes |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1776-1783 |
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Abstract |
Recent progress in the field of human action recognition points towards the use of Spatio-Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this paper we present a new approach for STIP detection by applying surround suppression combined with local and temporal constraints. Our method is significantly different from existing STIP detectors and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-visual words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on existing benchmark datasets, and more challenging datasets of complex scenes, validate our approach and show state-of-the-art performance. |
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Address |
Barcelona |
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ISSN |
1550-5499 |
ISBN |
978-1-4577-1101-5 |
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Conference |
ICCV |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ CHM2011 |
Serial |
1811 |
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Permanent link to this record |
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Author |
Xavier Carrillo; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; Petia Radeva; Neus Salvatella; Oriol Pujol; J. Mauri; A. Bayes |
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Title |
Changes in Radial Artery Volume Assessed Using Intravascular Ultrasound: A Comparison of Two Vasodilator Regimens in Transradial Coronary Intervention |
Type |
Journal Article |
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Year |
2011 |
Publication |
Journal of Invasive Cardiology |
Abbreviated Journal |
JOIC |
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Volume |
23 |
Issue |
10 |
Pages |
401-404 |
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Keywords |
radial; vasodilator treatment; percutaneous coronary intervention; IVUS; volumetric IVUS analysis |
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Abstract |
OBJECTIVES:
This study used intravascular ultrasound (IVUS) to evaluate radial artery volume changes after intraarterial administration of nitroglycerin and/or verapamil.
BACKGROUND:
Radial artery spasm, which is associated with radial artery size, is the main limitation of the transradial approach in percutaneous coronary interventions (PCI).
METHODS:
This prospective, randomized study compared the effect of two intra-arterial vasodilator regimens on radial artery volume: 0.2 mg of nitroglycerin plus 2.5 mg of verapamil (Group 1; n = 15) versus 2.5 mg of verapamil alone (Group 2; n = 15). Radial artery lumen volume was assessed using IVUS at two time points: at baseline (5 minutes after sheath insertion) and post-vasodilator (1 minute after drug administration). The luminal volume of the radial artery was computed using ECOC Random Fields (ECOC-RF), a technique used for automatic segmentation of luminal borders in longitudinal cut images from IVUS sequences.
RESULTS:
There was a significant increase in arterial lumen volume in both groups, with an increase from 451 ± 177 mm³ to 508 ± 192 mm³ (p = 0.001) in Group 1 and from 456 ± 188 mm³ to 509 ± 170 mm³ (p = 0.001) in Group 2. There were no significant differences between the groups in terms of absolute volume increase (58 mm³ versus 53 mm³, respectively; p = 0.65) or in relative volume increase (14% versus 20%, respectively; p = 0.69).
CONCLUSIONS:
Administration of nitroglycerin plus verapamil or verapamil alone to the radial artery resulted in similar increases in arterial lumen volume according to ECOC-RF IVUS measurements. |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CFC2011 |
Serial |
1797 |
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Permanent link to this record |
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Author |
Pierluigi Casale |
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Title |
Approximate Ensemble Methods for Physical Activity Recognition Applications |
Type |
Book Whole |
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Year |
2011 |
Publication |
PhD Thesis, Universitat de Barcelona-CVC |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
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Abstract |
The main interest of this thesis focuses on computational methodologies able to
reduce the degree of complexity of learning algorithms and its application to physical
activity recognition.
Random Projections will be used to reduce the computational complexity in Multiple Classifier Systems. A new boosting algorithm and a new one-class classification
methodology have been developed. In both cases, random projections are used for
reducing the dimensionality of the problem and for generating diversity, exploiting in
this way the benefits that ensembles of classifiers provide in terms of performances
and stability. Moreover, the new one-class classification methodology, based on an ensemble strategy able to approximate a multidimensional convex-hull, has been proved
to over-perform state-of-the-art one-class classification methodologies.
The practical focus of the thesis is towards Physical Activity Recognition. A new
hardware platform for wearable computing application has been developed and used
for collecting data of activities of daily living allowing to study the optimal features
set able to successful classify activities.
Based on the classification methodologies developed and the study conducted on
physical activity classification, a machine learning architecture capable to provide a
continuous authentication mechanism for mobile-devices users has been worked out,
as last part of the thesis. The system, based on a personalized classifier, states on
the analysis of the characteristic gait patterns typical of each individual ensuring an
unobtrusive and continuous authentication mechanism |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Oriol Pujol;Petia Radeva |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ Cas2011 |
Serial |
1837 |
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Permanent link to this record |
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Author |
Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera |
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Title |
Introducing the Separability Matrix for Error Correcting Output Codes Coding |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International Conference on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
227-236 |
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Keywords |
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Abstract |
Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results. |
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Address |
Napoles, Italy |
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Corporate Author |
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Thesis |
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Publisher |
Springer-Verlag Berlin, Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21556-8 |
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Conference |
MCS |
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Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ BPB2011b |
Serial |
1887 |
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Permanent link to this record |
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Author |
Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera |
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Title |
Introducing the Separability Matrix for Error Correcting Output Codes Coding |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International conference on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
227-236 |
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Keywords |
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Abstract |
Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results. |
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Address |
Napoles, Italy |
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Corporate Author |
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Thesis |
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Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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ISBN |
978-3-642-21556-8 |
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MCS |
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Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ BPB2011a |
Serial |
1771 |
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Permanent link to this record |
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Author |
Simone Balocco; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva |
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Title |
Plaque Type, Plaque Burden and Wall Shear Stress Relation in Coronary Arteries Assessed by X-ray Angiography and Intravascular Ultrasound: a Qualitative Study |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Symposium on Applied Sciences in Biomedical and Communication Technologies |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
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Abstract |
In this paper, we present a complete framework that automatically provides fluid-dynamic and plaque analysis from IVUS and Angiographic sequences. Such framework is used to analyze, in three coronary arteries, the relation between wall shear stress with type and amount of plaque. Preliminary qualitative results show an inverse relation between the wall shear stress and the plaque burden, which is confirmed by the fact that the plaque growth is higher on the wall having concave curvature. Regarding the plaque type it was observed that regions having low shear stress are predominantly fibro-lipidic while the heavy calcifications are in general located in areas of the vessel having high WSS. |
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ISBN |
978-1-4503-0913-4 |
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Conference |
ISABEL |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ BGC2011b |
Serial |
1799 |
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Permanent link to this record |
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Author |
Simone Balocco; Carlo Gatta; Francesco Ciompi; Oriol Pujol; Xavier Carrillo; J. Mauri; Petia Radeva |
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Title |
Combining Growcut and Temporal Correlation for IVUS Lumen Segmentation |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
556-563 |
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Abstract |
The assessment of arterial luminal area, performed by IVUS analysis, is a clinical index used to evaluate the degree of coronary artery disease. In this paper we propose a novel approach to automatically segment the vessel lumen, which combines model-based temporal information extracted from successive frames of the sequence, with spatial classification using the Growcut algorithm. The performance of the method is evaluated by an in vivo experiment on 300 IVUS frames. The automatic and manual segmentation performances in general vessel and stent frames are comparable. The average segmentation error in vessel, stent and bifurcation frames are 0.17±0.08 mm, 0.18±0.07 mm and 0.31±0.12 mm respectively. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Corporate Author |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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Language |
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Summary Language |
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Series Editor |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ BGC2011a |
Serial |
1741 |
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Permanent link to this record |
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Author |
Shida Beigpour; Joost Van de Weijer |
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Title |
Object Recoloring Based on Intrinsic Image Estimation |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th IEEE International Conference in Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
327 - 334 |
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Abstract |
Object recoloring is one of the most popular photo-editing tasks. The problem of object recoloring is highly under-constrained, and existing recoloring methods limit their application to objects lit by a white illuminant. Application of these methods to real-world scenes lit by colored illuminants, multiple illuminants, or interreflections, results in unrealistic recoloring of objects. In this paper, we focus on the recoloring of single-colored objects presegmented from their background. The single-color constraint allows us to fit a more comprehensive physical model to the object. We demonstrate that this permits us to perform realistic recoloring of objects lit by non-white illuminants, and multiple illuminants. Moreover, the model allows for more realistic handling of illuminant alteration of the scene. Recoloring results captured by uncalibrated cameras demonstrate that the proposed framework obtains realistic recoloring for complex natural images. Furthermore we use the model to transfer color between objects and show that the results are more realistic than existing color transfer methods. |
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Barcelona |
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ISSN |
1550-5499 |
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978-1-4577-1101-5 |
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ICCV |
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CIC |
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Call Number |
Admin @ si @ BeW2011 |
Serial |
1781 |
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Author |
Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva |
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Title |
On the Design of Low Redundancy Error-Correcting Output Codes |
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Book Chapter |
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Year |
2011 |
Publication |
Ensembles in Machine Learning Applications |
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Volume |
373 |
Issue |
2 |
Pages |
21-38 |
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Abstract |
The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers. |
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Springer Berlin Heidelberg |
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1860-949X |
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978-3-642-22909-1 |
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MILAB; OR;HuPBA;MV |
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Admin @ si @ BEB2011b |
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1886 |
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Author |
Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Petia Radeva; Jordi Vitria; Oriol Pujol |
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Title |
Minimal Design of Error-Correcting Output Codes |
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Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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33 |
Issue |
6 |
Pages |
693-702 |
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Keywords |
Multi-class classification; Error-correcting output codes; Ensemble of classifiers |
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Abstract |
IF JCR CCIA 1.303 2009 54/103
The classification of large number of object categories is a challenging trend in the pattern recognition field. In literature, this is often addressed using an ensemble of classifiers. In this scope, the Error-correcting output codes framework has demonstrated to be a powerful tool for combining classifiers. However, most state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best minimal ECOC code configuration. The results over several public UCI datasets and different multi-class computer vision problems show that the proposed methodology obtains comparable (even better) results than state-of-the-art ECOC methodologies with far less number of dichotomizers. |
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Elsevier |
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0167-8655 |
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Notes |
MILAB; OR;HuPBA;MV |
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Call Number |
Admin @ si @ BEB2011a |
Serial |
1800 |
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