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Author Ernest Valveny; Enric Marti edit   pdf
doi  isbn
openurl 
  Title Hand-drawn symbol recognition in graphic documents using deformable template matching and a Bayesian framework Type Conference Article
  Year 2000 Publication Proc. 15th Int Pattern Recognition Conf Abbreviated Journal  
  Volume 2 Issue (up) Pages 239-242  
  Keywords  
  Abstract Hand-drawn symbols can take many different and distorted shapes from their ideal representation. Then, very flexible methods are needed to be able to handle unconstrained drawings. We propose here to extend our previous work in hand-drawn symbol recognition based on a Bayesian framework and deformable template matching. This approach gets flexibility enough to fit distorted shapes in the drawing while keeping fidelity to the ideal shape of the symbol. In this work, we define the similarity measure between an image and a symbol based on the distance from every pixel in the image to the lines in the symbol. Matching is carried out using an implementation of the EM algorithm. Thus, we can improve recognition rates and computation time with respect to our previous formulation based on a simulated annealing algorithm.  
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  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 0-7695-0750-6 Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM2000 Serial 1656  
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Author Ernest Valveny; Enric Marti edit   pdf
url  doi
openurl 
  Title Application of deformable template matching to symbol recognition in hand-written architectural draw Type Conference Article
  Year 1999 Publication Proceedings of the Fifth International Conference on Abbreviated Journal  
  Volume Issue (up) Pages  
  Keywords  
  Abstract We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Bangalore (India) 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 DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999a Serial 1657  
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Author Ernest Valveny; Enric Marti edit  openurl
  Title Recognition of lineal symbols in hand-written drawings using deformable template matching Type Conference Article
  Year 1999 Publication Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes Abbreviated Journal  
  Volume Issue (up) Pages  
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  Publisher Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999 Serial 1658  
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Author Ernest Valveny; Enric Marti edit  openurl
  Title Dimensions analysis in hand-drawn architectural drawings Type Conference Article
  Year 1997 Publication VII National Simposium of Pattern Recognition and image Analysis, SNRFAI´97 Abbreviated Journal  
  Volume Issue (up) Pages 90-91  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication CVC-UAB 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 DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1997 Serial 1659  
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Author Ernest Valveny; Ricardo Toledo; Ramon Baldrich; Enric Marti edit  openurl
  Title Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching Type Conference Article
  Year 2002 Publication Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 Abbreviated Journal  
  Volume Issue (up) Pages 502–507  
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  Publisher Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;RV;CAT;IAM;;CIC;ADAS Approved no  
  Call Number IAM @ iam @ VTB2002 Serial 1660  
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Author Sergio Vera edit   pdf
openurl 
  Title Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 164 Issue (up) Pages  
  Keywords Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score  
  Abstract Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research.  
  Address  
  Corporate Author Thesis Master's thesis  
  Publisher Place of Publication Bellaterra 01893, Barcelona, Spain 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 IAM Approved no  
  Call Number IAM @ iam @ Ver2010 Serial 1661  
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Author Fernando Vilariño; Debora Gil; Petia Radeva edit   pdf
url  isbn
openurl 
  Title A Novel FLDA Formulation for Numerical Stability Analysis Type Book Chapter
  Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal  
  Volume 113 Issue (up) Pages 77-84  
  Keywords Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision  
  Abstract Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.  
  Address  
  Corporate Author Thesis  
  Publisher IOS Press Place of Publication Editor J. Vitrià, P. Radeva and I. Aguiló  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-58603-466-5 Medium  
  Area Expedition Conference  
  Notes MV;IAM;MILAB Approved no  
  Call Number IAM @ iam @ VGR2004 Serial 1663  
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Author Fernando Vilariño; Enric Marti edit  openurl
  Title New didactic techniques in the EHES applying mobile technologies Type Miscellaneous
  Year 2008 Publication Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya Abbreviated Journal  
  Volume Issue (up) Pages  
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  Corporate Author Agencia de Gestió d’Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya Expedition Conference  
  Notes MILAB;IAM;MV; Approved no  
  Call Number IAM @ iam @ VIM2008 Serial 1664  
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Author Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie edit   pdf
url  openurl
  Title Inferring the Performance of Medical Imaging Algorithms Type Conference Article
  Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 6854 Issue (up) Pages 520-528  
  Keywords Validation, Statistical Inference, Medical Imaging Algorithms.  
  Abstract Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence.
 
  Address Sevilla  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Berlin Editor Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch  
  Language Summary Language Original Title  
  Series Editor Series Title L Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CAIP  
  Notes IAM; ADAS Approved no  
  Call Number IAM @ iam @ HGR2011 Serial 1676  
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Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
url  isbn
openurl 
  Title An inference model for analyzing termination conditions of Evolutionary Algorithms Type Conference Article
  Year 2011 Publication 14th Congrès Català en Intel·ligencia Artificial Abbreviated Journal  
  Volume Issue (up) Pages 216-225  
  Keywords Evolutionary Computation Convergence, Termination Conditions, Statistical Inference  
  Abstract In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution.
 
  Address Lleida, Catalonia (Spain)  
  Corporate Author Associació Catalana Intel·ligència Artificial 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 978-1-60750-841-0 Medium  
  Area Expedition Conference CCIA  
  Notes IAM Approved no  
  Call Number IAM @ iam @ RGG2011a Serial 1677  
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