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Author M. Bressan; Jordi Vitria edit  doi
openurl 
  Title Nonparametric Discriminant Analysis and Nearest Neighbor Classification Type (up) Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue 15 Pages 2743–2749  
  Keywords  
  Abstract IF: 0.809  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BrV2003b Serial 367  
Permanent link to this record
 
 
Author David Guillamet; Jordi Vitria edit  doi
openurl 
  Title Evaluation of distance metrics for recognition based on non-negative matrix factorization Type (up) Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue 9-10 Pages 1599 –1605  
  Keywords  
  Abstract IF: 0.809  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ GuV2003b Serial 380  
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Author David Guillamet; Jordi Vitria; B. Shiele edit  doi
openurl 
  Title Introducing a weighted non-negative matrix factorization for image classification Type (up) Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue 14 Pages 2447–2454  
  Keywords  
  Abstract IF: 0.809  
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  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 @ GVS2003 Serial 382  
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Author Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva edit  doi
openurl 
  Title ROC curves and video analysis optimization in intestinal capsule endoscopy Type (up) 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.  
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  ISSN ISBN Medium  
  Area 800 Expedition Conference  
  Notes MILAB;MV;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006 Serial 647  
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Author Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Fernando Azpiroz; Petia Radeva; Jordi Vitria edit   pdf
doi  openurl
  Title Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images Type (up) Journal Article
  Year 2014 Publication IEEE Transactions on Information Technology in Biomedicine Abbreviated Journal TITB  
  Volume 18 Issue 6 Pages 1831-1838  
  Keywords Wireless Capsule Endoscopy; Small Bowel Motility Dysfunction; Contraction Detection; Structured Prediction; Betweenness Centrality  
  Abstract Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state of the art performance for this task.  
  Address  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR; MILAB; 600.046;MV Approved no  
  Call Number Admin @ si @ SDZ2014 Serial 2385  
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