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Author H.Martin Kjer; Jens Fagertuna; Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester; Rasmus R. Paulsena edit   pdf
url  openurl
  Title Free-form image registration of human cochlear uCT data using skeleton similarity as anatomical prior Type Journal Article
  Year (down) 2016 Publication Patter Recognition Letters Abbreviated Journal PRL  
  Volume 76 Issue 1 Pages 76-82  
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  Notes IAM; 600.060 Approved no  
  Call Number Admin @ si @ MFV2017b Serial 2941  
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Author Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso; Vanesa Vicens; Cubero Noelia; Rosa Lopez Lisbona; Carles Sanchez; Agnes Borras; Antoni Rosell edit  url
openurl 
  Title Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation Type Journal Article
  Year (down) 2016 Publication Chest Journal Abbreviated Journal CHEST  
  Volume 150 Issue 4 Pages 1003A  
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  Notes IAM; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ DGC2016 Serial 3099  
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Author Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Antoni Rosell; Marta Diez-Ferrer; Debora Gil edit   pdf
doi  openurl
  Title Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy Type Journal Article
  Year (down) 2015 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCAR  
  Volume 10 Issue 6 Pages 935-945  
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  Notes IAM; MV; 600.075 Approved no  
  Call Number Admin @ si @ SBS2015a Serial 2611  
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Author Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; J.Roncaries; Debora Gil edit  doi
openurl 
  Title Automatic evaluation of practices in Moodle for Self Learning in Engineering Type Journal
  Year (down) 2015 Publication Journal of Technology and Science Education Abbreviated Journal JOTSE  
  Volume 5 Issue 2 Pages 97-106  
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  Notes IAM; DAG; 600.075; 600.077 Approved no  
  Call Number Admin @ si @ SRM2015 Serial 2610  
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Author Debora Gil; David Roche; Agnes Borras; Jesus Giraldo edit  doi
openurl 
  Title Terminating Evolutionary Algorithms at their Steady State Type Journal Article
  Year (down) 2015 Publication Computational Optimization and Applications Abbreviated Journal COA  
  Volume 61 Issue 2 Pages 489-515  
  Keywords Evolutionary algorithms; Termination condition; Steady state; Differential evolution  
  Abstract Assessing the reliability of termination conditions for evolutionary algorithms (EAs) is of prime importance. An erroneous or weak stop criterion can negatively affect both the computational effort and the final result. We introduce a statistical framework for assessing whether a termination condition is able to stop an EA at its steady state, so that its results can not be improved anymore. We use a regression model in order to determine the requirements ensuring that a measure derived from EA evolving population is related to the distance to the optimum in decision variable space. Our framework is analyzed across 24 benchmark test functions and two standard termination criteria based on function fitness value in objective function space and EA population decision variable space distribution for the differential evolution (DE) paradigm. Results validate our framework as a powerful tool for determining the capability of a measure for terminating EA and the results also identify the decision variable space distribution as the best-suited for accurately terminating DE in real-world applications.  
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  Publisher Springer US Place of Publication Editor  
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  ISSN 0926-6003 ISBN Medium  
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  Notes IAM; 600.044; 605.203; 600.060; 600.075 Approved no  
  Call Number Admin @ si @ GRB2015 Serial 2560  
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