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Author Neus Salvatella; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; H. Tizon; Xavier Carrillo; J. Mauri; Petia Radeva edit  doi
openurl 
  Title Radial Artery Volume Changes After Administration Of Two Different Intra-arterial Drug Regimens. Assessment by Intravascular Ultrasound Type Journal Article
  Year 2010 Publication Journal of the American College of Cardiology Abbreviated Journal JACC  
  Volume 56 Issue (up) 13s1 Pages B119  
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  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SFC2010b Serial 1364  
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Author Jordi Vitria; J. Llacer edit  doi
openurl 
  Title Reconstructing 3D light microscopic images using the EM algorithm Type Journal
  Year 1996 Publication Pattern Recognition Letters Abbreviated Journal  
  Volume 17 Issue (up) 14 Pages 1491–1498  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ ViL1996 Serial 74  
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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 Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue (up) 14 Pages 2447–2454  
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  Abstract IF: 0.809  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ GVS2003 Serial 382  
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Author Xavier Otazu; Oriol Pujol edit  doi
openurl 
  Title Wavelet based approach to cluster analysis. Application on low dimensional data sets Type Journal Article
  Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 27 Issue (up) 14 Pages 1590–1605  
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  Notes MILAB; CIC; HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ OtP2006 Serial 658  
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Author Josep Llados; Horst Bunke; Enric Marti edit   pdf
url  doi
openurl 
  Title Finding rotational symmetries by cyclic string matching Type Journal Article
  Year 1997 Publication Pattern recognition letters Abbreviated Journal PRL  
  Volume 18 Issue (up) 14 Pages 1435-1442  
  Keywords Rotational symmetry; Reflectional symmetry; String matching  
  Abstract Symmetry is an important shape feature. In this paper, a simple and fast method to detect perfect and distorted rotational symmetries of 2D objects is described. The boundary of a shape is polygonally approximated and represented as a string. Rotational symmetries are found by cyclic string matching between two identical copies of the shape string. The set of minimum cost edit sequences that transform the shape string to a cyclically shifted version of itself define the rotational symmetry and its order. Finally, a modification of the algorithm is proposed to detect reflectional symmetries. Some experimental results are presented to show the reliability of the proposed algorithm  
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  Publisher Elsevier Place of Publication Editor  
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  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LBM1997a Serial 1562  
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Author Fadi Dornaika; Bogdan Raducanu edit  doi
isbn  openurl
  Title Subtle Facial Expression Recognition in Still Images and Videos Type Book Chapter
  Year 2011 Publication Advances in Face Image Analysis: Techniques and Technologies Abbreviated Journal  
  Volume Issue (up) 14 Pages 259-277  
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  Abstract This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM).  
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  Publisher IGI-Global Place of Publication New York, USA Editor Yu-Jin Zhang  
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  ISSN ISBN 978-1-6152-0991-0 Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ DoR2011 Serial 1751  
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Author M. Bressan; Jordi Vitria edit  doi
openurl 
  Title Nonparametric Discriminant Analysis and Nearest Neighbor Classification Type Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue (up) 15 Pages 2743–2749  
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  Abstract IF: 0.809  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BrV2003b Serial 367  
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Author Antonio Lopez; Felipe Lumbreras; Joan Serrat edit  openurl
  Title Efficient computation of local creaseness Type Report
  Year 1997 Publication CVC Technical Report Abbreviated Journal  
  Volume Issue (up) 15 Pages  
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  Publisher Place of Publication CVC, Bellaterra (Spain) Editor  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ LLS1997b Serial 527  
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Author Fadi Dornaika; Angel Sappa edit  doi
openurl 
  Title Rigid and Non-rigid Face Motion Tracking by Aligning Texture Maps and Stereo 3D Models Type Journal Article
  Year 2007 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 28 Issue (up) 15 Pages 2116-2126  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ DoS2007c Serial 877  
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Author Sergio Escalera; Alicia Fornes; O. Pujol; Petia Radeva; Gemma Sanchez; Josep Llados edit  doi
openurl 
  Title Blurred Shape Model for Binary and Grey-level Symbol Recognition Type Journal Article
  Year 2009 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 30 Issue (up) 15 Pages 1424–1433  
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  Abstract Many symbol recognition problems require the use of robust descriptors in order to obtain rich information of the data. However, the research of a good descriptor is still an open issue due to the high variability of symbols appearance. Rotation, partial occlusions, elastic deformations, intra-class and inter-class variations, or high variability among symbols due to different writing styles, are just a few problems. In this paper, we introduce a symbol shape description to deal with the changes in appearance that these types of symbols suffer. The shape of the symbol is aligned based on principal components to make the recognition invariant to rotation and reflection. Then, we present the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape. Moreover, we include the new descriptor in a system to deal with multi-class symbol categorization problems. Adaboost is used to train the binary classifiers, learning the BSM features that better split symbol classes. Then, the binary problems are embedded in an Error-Correcting Output Codes framework (ECOC) to deal with the multi-class case. The methodology is evaluated on different synthetic and real data sets. State-of-the-art descriptors and classifiers are compared, showing the robustness and better performance of the present scheme to classify symbols with high variability of appearance.  
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  Notes HuPBA; DAG; MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ EFP2009a Serial 1180  
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Author Ernest Valveny; Enric Marti edit   pdf
doi  openurl
  Title A model for image generation and symbol recognition through the deformation of lineal shapes Type Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue (up) 15 Pages 2857-2867  
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  Abstract We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents.  
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  Publisher Elsevier Science Inc. Place of Publication New York, NY, USA Editor  
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  ISSN 0167-8655 ISBN Medium  
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  Notes DAG; IAM Approved no  
  Call Number IAM @ iam @ VAM2003 Serial 1653  
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Author Jaume Gibert; Ernest Valveny; Horst Bunke edit   pdf
doi  openurl
  Title Feature Selection on Node Statistics Based Embedding of Graphs Type Journal Article
  Year 2012 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 33 Issue (up) 15 Pages 1980–1990  
  Keywords Structural pattern recognition; Graph embedding; Feature ranking; PCA; Graph classification  
  Abstract Representing a graph with a feature vector is a common way of making statistical machine learning algorithms applicable to the domain of graphs. Such a transition from graphs to vectors is known as graphembedding. A key issue in graphembedding is to select a proper set of features in order to make the vectorial representation of graphs as strong and discriminative as possible. In this article, we propose features that are constructed out of frequencies of node label representatives. We first build a large set of features and then select the most discriminative ones according to different ranking criteria and feature transformation algorithms. On different classification tasks, we experimentally show that only a small significant subset of these features is needed to achieve the same classification rates as competing to state-of-the-art methods.  
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  Notes DAG Approved no  
  Call Number Admin @ si @ GVB2012b Serial 1993  
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Author Cristina Cañero; Petia Radeva edit  doi
openurl 
  Title Vesselness enhancement diffusion Type Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue (up) 16 Pages 3141–3151  
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  Abstract IF: 0.809  
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  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ CaR2003 Serial 371  
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Author Joan Marc Llargues Asensio; Juan Peralta; Raul Arrabales; Manuel Gonzalez Bedia; Paulo Cortez; Antonio Lopez edit  doi
openurl 
  Title Artificial Intelligence Approaches for the Generation and Assessment of Believable Human-Like Behaviour in Virtual Characters Type Journal Article
  Year 2014 Publication Expert Systems With Applications Abbreviated Journal EXSY  
  Volume 41 Issue (up) 16 Pages 7281–7290  
  Keywords Turing test; Human-like behaviour; Believability; Non-player characters; Cognitive architectures; Genetic algorithm; Artificial neural networks  
  Abstract Having artificial agents to autonomously produce human-like behaviour is one of the most ambitious original goals of Artificial Intelligence (AI) and remains an open problem nowadays. The imitation game originally proposed by Turing constitute a very effective method to prove the indistinguishability of an artificial agent. The behaviour of an agent is said to be indistinguishable from that of a human when observers (the so-called judges in the Turing test) cannot tell apart humans and non-human agents. Different environments, testing protocols, scopes and problem domains can be established to develop limited versions or variants of the original Turing test. In this paper we use a specific version of the Turing test, based on the international BotPrize competition, built in a First-Person Shooter video game, where both human players and non-player characters interact in complex virtual environments. Based on our past experience both in the BotPrize competition and other robotics and computer game AI applications we have developed three new more advanced controllers for believable agents: two based on a combination of the CERA–CRANIUM and SOAR cognitive architectures and other based on ADANN, a system for the automatic evolution and adaptation of artificial neural networks. These two new agents have been put to the test jointly with CCBot3, the winner of BotPrize 2010 competition (Arrabales et al., 2012), and have showed a significant improvement in the humanness ratio. Additionally, we have confronted all these bots to both First-person believability assessment (BotPrize original judging protocol) and Third-person believability assessment, demonstrating that the active involvement of the judge has a great impact in the recognition of human-like behaviour.  
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  Notes ADAS; 600.055; 600.057; 600.076 Approved no  
  Call Number Admin @ si @ LPA2014 Serial 2500  
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Author Angel Morera; Angel Sanchez; A. Belen Moreno; Angel Sappa; Jose F. Velez edit   pdf
url  openurl
  Title SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities Type Journal Article
  Year 2020 Publication Sensors Abbreviated Journal SENS  
  Volume 20 Issue (up) 16 Pages 4587  
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  Abstract This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO) deep neural networks for the outdoor advertisement panel detection problem by handling multiple and combined variabilities in the scenes. Publicity panel detection in images offers important advantages both in the real world as well as in the virtual one. For example, applications like Google Street View can be used for Internet publicity and when detecting these ads panels in images, it could be possible to replace the publicity appearing inside the panels by another from a funding company. In our experiments, both SSD and YOLO detectors have produced acceptable results under variable sizes of panels, illumination conditions, viewing perspectives, partial occlusion of panels, complex background and multiple panels in scenes. Due to the difficulty of finding annotated images for the considered problem, we created our own dataset for conducting the experiments. The major strength of the SSD model was the almost elimination of False Positive (FP) cases, situation that is preferable when the publicity contained inside the panel is analyzed after detecting them. On the other side, YOLO produced better panel localization results detecting a higher number of True Positive (TP) panels with a higher accuracy. Finally, a comparison of the two analyzed object detection models with different types of semantic segmentation networks and using the same evaluation metrics is also included.  
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  Notes MSIAU; 600.130; 601.349; 600.122 Approved no  
  Call Number Admin @ si @ MSM2020 Serial 3452  
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