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Author
A. Martinez; Jordi Vitria
Title
Learning mixture models using a genetic version of the EM algorithm.
Type
Journal Article
Year
2000
Publication
Pattern Recognition Letters
Abbreviated Journal
PRL
Volume
21
Issue
8
Pages
759–769
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
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ MVi2000
Serial
335
Permanent link to this record
Author
F. Moreso; D. Seron; Jordi Vitria; J.M. Grinyo; F.M. Colome-Serra; N. Pares; J.R. Serra
Title
Quantification of Interstitial Chronic Renal Damage by means of Texture Analysis.
Type
Journal Article
Year
1994
Publication
Kidney International
Abbreviated Journal
Volume
46
Issue
6
Pages
1721-1727
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
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ MSV1994
Serial
113
Permanent link to this record
Author
David Masip; Agata Lapedriza; Jordi Vitria
Title
Boosted Online Learning for Face Recognition
Type
Journal Article
Year
2009
Publication
IEEE Transactions on Systems, Man and Cybernetics part B
Abbreviated Journal
TSMCB
Volume
39
Issue
2
Pages
530–538
Keywords
Abstract
Face recognition applications commonly suffer from three main drawbacks: a reduced training set, information lying in high-dimensional subspaces, and the need to incorporate new people to recognize. In the recent literature, the extension of a face classifier in order to include new people in the model has been solved using online feature extraction techniques. The most successful approaches of those are the extensions of the principal component analysis or the linear discriminant analysis. In the current paper, a new online boosting algorithm is introduced: a face recognition method that extends a boosting-based classifier by adding new classes while avoiding the need of retraining the classifier each time a new person joins the system. The classifier is learned using the multitask learning principle where multiple verification tasks are trained together sharing the same feature space. The new classes are added taking advantage of the structure learned previously, being the addition of new classes not computationally demanding. The present proposal has been (experimentally) validated with two different facial data sets by comparing our approach with the current state-of-the-art techniques. The results show that the proposed online boosting algorithm fares better in terms of final accuracy. In addition, the global performance does not decrease drastically even when the number of classes of the base problem is multiplied by eight.
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
1083–4419
ISBN
Medium
Area
Expedition
Conference
Notes
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ MLV2009
Serial
1155
Permanent link to this record
Author
David Masip; Ludmila I. Kuncheva; Jordi Vitria
Title
An ensemble-based method for linear feature extraction for two-class problems
Type
Journal
Year
2005
Publication
Pattern Analysis and Applications, 8(3): 227–237 (IF: 0.782)
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
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ MKV2005
Serial
613
Permanent link to this record
Author
David Masip; M. Bressan; Jordi Vitria
Title
Feature extraction methods for real-time face detection and classification
Type
Journal
Year
2005
Publication
Eurasip Journal on Applied Signal Processing, 13: 2061–2071
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
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ MBV2005
Serial
612
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