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Author Gloria Fernandez Esparrach; Jorge Bernal; Maria Lopez Ceron; Henry Cordova; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; F. Javier Sanchez edit   pdf
doi  openurl
  Title Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps Type Journal Article
  Year 2016 Publication Endoscopy Abbreviated Journal END  
  Volume 48 Issue 9 Pages 837-842  
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  Abstract Background and aims: Polyp miss-rate is a drawback of colonoscopy that increases significantly in small polyps. We explored the efficacy of an automatic computer vision method for polyp detection.
Methods: Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps which represent the likelihood of polyp presence.
Results: In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. Mean values of the maximum of energy map were higher in frames with polyps than without (p<0.001). Performance improved in high quality frames (AUC= 0.79, 95%CI: 0.70-0.87 vs 0.75, 95%CI: 0.66-0.83). Using 3.75 as maximum threshold value, sensitivity and specificity for detection of polyps were 70.4% (95%CI: 60.3-80.8) and 72.4% (95%CI: 61.6-84.6), respectively.
Conclusion: Energy maps showed a good performance for colonic polyp detection. This indicates a potential applicability in clinical practice.
 
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  Call Number (up) Admin @ si @FBL2016 Serial 2778  
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Author Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification Type Journal Article
  Year 2009 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS  
  Volume 10 Issue 1 Pages 113–126  
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  Abstract The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, we introduce a novel approach for the detection and classification of traffic signs. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost, which allows the use of large feature spaces. Classification is defined as a multiclass categorization problem. A battery of classifiers is trained to split classes in an Error-Correcting Output Code (ECOC) framework. We propose an ECOC design through a forest of optimal tree structures that are embedded in the ECOC matrix. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination.  
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  ISSN 1524-9050 ISBN Medium  
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  Notes OR;MILAB;HuPBA;MV Approved no  
  Call Number (up) BCNPCL @ bcnpcl @ BEV2008 Serial 1116  
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Author M. Bressan; David Guillamet; Jordi Vitria edit  openurl
  Title Using an ICA Representation of Local Color Histograms for Object Recognition Type Journal
  Year 2003 Publication Pattern Recognition, 36(3):691–701 (IF: 1.611) Abbreviated Journal  
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  Notes OR;MV Approved no  
  Call Number (up) BCNPCL @ bcnpcl @ BGV2003 Serial 365  
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Author M. Bressan; David Guillamet; Jordi Vitria edit  openurl
  Title Multiclass Object Recognition using Class-Conditional Independent Component Analisis Type Journal
  Year 2004 Publication Cybernetics and Systems, 35/1:35–61 (IF: 0.768) Abbreviated Journal  
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  Notes OR;MV Approved no  
  Call Number (up) BCNPCL @ bcnpcl @ BGV2004 Serial 442  
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Author M. Bressan; Jordi Vitria edit  openurl
  Title Independent Component Analysis and Naïve Bayes Classification. Type Journal Article
  Year 2002 Publication Proceedings of the Second IASTED International Conference Visualilzation, Imaging and Image Proceesing VIIP 2002: 496–501. Abbreviated Journal  
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  Notes OR;MV Approved no  
  Call Number (up) BCNPCL @ bcnpcl @ BrV2002a Serial 288  
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