Search & Display Options
Search within Results:
Field:
author
title
year
keywords
abstract
type
contains:
...
Exclude matches
Display Options:
Field:
all fields
keywords & abstract
additional fields
records per page
Select All
Deselect All
[1–10]
<<
11
12
13
14
15
16
17
18
19
20
>>
[21–21]
List View
|
Citations
|
Details
Records
Links
Author
A. Pujol; Jordi Vitria; Felipe Lumbreras; Juan J. Villanueva
Title
Topological principal component analysis for face encoding and recognition
Type
Journal Article
Year
2001
Publication
Pattern Recognition Letters
Abbreviated Journal
PRL
Volume
22
Issue
6-7
Pages
769–776
Keywords
Abstract
IF: 0.552
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
ADAS;OR;MV
Approved
no
Call Number
ADAS @ adas @ PVL2001
Serial
155
Permanent link to this record
Author
Bogdan Raducanu; Jordi Vitria; Ales Leonardis
Title
Online pattern recognition and machine learning techniques for computer-vision: Theory and applications
Type
Journal Article
Year
2010
Publication
Image and Vision Computing
Abbreviated Journal
IMAVIS
Volume
28
Issue
7
Pages
1063–1064
Keywords
Abstract
(Editorial for the Special Issue on Online pattern recognition and machine learning techniques)
In real life, visual learning is supposed to be a continuous process. This paradigm has found its way also in artificial vision systems. There is an increasing trend in pattern recognition represented by online learning approaches, which aims at continuously updating the data representation when new information arrives. Starting with a minimal dataset, the initial knowledge is expanded by incorporating incoming instances, which may have not been previously available or foreseen at the system’s design stage. An interesting characteristic of this strategy is that the train and test phases take place simultaneously. Given the increasing interest in this subject, the aim of this special issue is to be a landmark event in the development of online learning techniques and their applications with the hope that it will capture the interest of a wider audience and will attract even more researchers. We received 19 contributions, of which 9 have been accepted for publication, after having been subjected to usual peer review process.
Address
Corporate Author
Thesis
Publisher
Elsevier
Place of Publication
Editor
Language
Summary Language
Original Title
Series Editor
Series Title
Abbreviated Series Title
Series Volume
Series Issue
Edition
ISSN
0262-8856
ISBN
Medium
Area
Expedition
Conference
Notes
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ RVL2010
Serial
1280
Permanent link to this record
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
Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva
Title
ROC curves and video analysis optimization in intestinal capsule endoscopy
Type
Journal Article
Year
2006
Publication
Pattern Recognition Letters
Abbreviated Journal
PRL
Volume
27
Issue
8
Pages
875–881
Keywords
ROC curves; Classification; Classifiers ensemble; Detection of intestinal contractions; Imbalanced classes; Wireless capsule endoscopy
Abstract
Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions.
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
800
Expedition
Conference
Notes
MILAB;MV;SIAI
Approved
no
Call Number
BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006
Serial
647
Permanent link to this record
Author
Bogdan Raducanu; Jordi Vitria
Title
Learning to Learn: From Smarts Machines to Intelligent Machines
Type
Journal
Year
2008
Publication
Patter Recognition Letters
Abbreviated Journal
PRL
Volume
29
Issue
8
Pages
1024–1032
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 @ RaV2008a
Serial
950
Permanent link to this record
Select All
Deselect All
[1–10]
<<
11
12
13
14
15
16
17
18
19
20
>>
[21–21]
List View
|
Citations
|
Details