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Author Meritxell Vinyals; Arnau Ramisa; Ricardo Toledo edit  openurl
  Title (up) An Evaluation of an Object Recognition Schema using Multiple Region Detectors Type Book Chapter
  Year 2007 Publication Artificial Intelligence Research and Development, 163:213–222, ISBN: 978–1–58603–798–7, Proceedings of the 10th International Conference of the ACIA (CCIA’07) Abbreviated Journal  
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  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ VRT2007 Serial 898  
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Author David Guillamet; Jordi Vitria edit  openurl
  Title (up) An Experimental Evaluation of K-nn for Linear Transforms of Positive Data Type Book Chapter
  Year 2003 Publication In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science. 2652:317–325 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Springer-Verlag  
  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 @ GuV2003a Serial 379  
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Author Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel edit  openurl
  Title (up) An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres Type Book Chapter
  Year 2015 Publication The White Book on Public Library Network from Diputació de Barcelona Abbreviated Journal  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MV; DAG;SIAI Approved no  
  Call Number Admin @ si @VKC2015 Serial 2798  
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Author Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil edit   pdf
url  doi
isbn  openurl
  Title (up) An illumination model of the trachea appearance in videobronchoscopy images Type Book Chapter
  Year 2012 Publication Image Analysis and Recognition Abbreviated Journal LNCS  
  Volume 7325 Issue Pages 313-320  
  Keywords Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation  
  Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.
 
  Address Aveiro, Portugal  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium  
  Area 800 Expedition Conference ICIAR  
  Notes MV;IAM Approved no  
  Call Number IAM @ iam @ SSR2012 Serial 1898  
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Author Salvatore Tabbone; Oriol Ramos Terrades edit  doi
isbn  openurl
  Title (up) An Overview of Symbol Recognition Type Book Chapter
  Year 2014 Publication Handbook of Document Image Processing and Recognition Abbreviated Journal  
  Volume D Issue Pages 523-551  
  Keywords Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting  
  Abstract According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-85729-858-4 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ TaT2014 Serial 2489  
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Author Fadi Dornaika; Bogdan Raducanu edit   pdf
openurl 
  Title (up) Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation Type Book Chapter
  Year 2012 Publication Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions Abbreviated Journal  
  Volume Issue Pages 157-178  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher NOVA Publishers Place of Publication Editor S.E. Carter  
  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 Admin @ si @ DoR2012 Serial 2183  
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Author Alicia Fornes; Gemma Sanchez edit  doi
isbn  openurl
  Title (up) Analysis and Recognition of Music Scores Type Book Chapter
  Year 2014 Publication Handbook of Document Image Processing and Recognition Abbreviated Journal  
  Volume E Issue Pages 749-774  
  Keywords  
  Abstract The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-85729-860-7 Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.076; 600.077 Approved no  
  Call Number Admin @ si @ FoS2014 Serial 2484  
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Author Isabelle Guyon; Lisheng Sun Hosoya; Marc Boulle; Hugo Jair Escalante; Sergio Escalera; Zhengying Liu; Damir Jajetic; Bisakha Ray; Mehreen Saeed; Michele Sebag; Alexander R.Statnikov; Wei-Wei Tu; Evelyne Viegas edit  url
openurl 
  Title (up) Analysis of the AutoML Challenge Series 2015-2018. Type Book Chapter
  Year 2019 Publication Automated Machine Learning Abbreviated Journal  
  Volume Issue Pages 177-219  
  Keywords  
  Abstract The ChaLearn AutoML Challenge (The authors are in alphabetical order of last name, except the first author who did most of the writing and the second author who produced most of the numerical analyses and plots.) (NIPS 2015 – ICML 2016) consisted of six rounds of a machine learning competition of progressive difficulty, subject to limited computational resources. It was followed bya one-round AutoML challenge (PAKDD 2018). The AutoML setting differs from former model selection/hyper-parameter selection challenges, such as the one we previously organized for NIPS 2006: the participants aim to develop fully automated and computationally efficient systems, capable of being trained and tested without human intervention, with code submission. This chapter analyzes the results of these competitions and provides details about the datasets, which were not revealed to the participants. The solutions of the winners are systematically benchmarked over all datasets of all rounds and compared with canonical machine learning algorithms available in scikit-learn. All materials discussed in this chapter (data and code) have been made publicly available at http://automl.chalearn.org/.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title SSCML  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA; no proj Approved no  
  Call Number Admin @ si @ GHB2019 Serial 3330  
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Author Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva edit   pdf
doi  openurl
  Title (up) Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions Type Book Chapter
  Year 2006 Publication 9th International Conference on Medical Image Computing and Computer–Assisted Intervention Abbreviated Journal  
  Volume 4191 Issue Pages 161–168  
  Keywords  
  Abstract Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions.  
  Address Copenhagen (Denmark)  
  Corporate Author Thesis  
  Publisher Springer Verlag Place of Publication Berlin Heidelberg Editor R. Larsen, M. Nielsen, and J. Sporring  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference MICCAI06  
  Notes MV;OR;MILAB;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006 Serial 725  
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Author Debora Gil; Oriol Rodriguez-Leor; Petia Radeva; Aura Hernandez-Sabate edit   pdf
doi  isbn
openurl 
  Title (up) Assessing Artery Motion Compensation in IVUS Type Book Chapter
  Year 2007 Publication Computer Analysis Of Images And Patterns Abbreviated Journal LNCS  
  Volume 4673 Issue Pages 213-220  
  Keywords validation standards; quality measures; IVUS motion compensation; conservation laws; Fourier development  
  Abstract Cardiac dynamics suppression is a main issue for visual improvement and computation of tissue mechanical properties in IntraVascular UltraSound (IVUS). Although in recent times several motion compensation techniques have arisen, there is a lack of objective evaluation of motion reduction in in vivo pullbacks. We consider that the assessment protocol deserves special attention for the sake of a clinical applicability as reliable as possible. Our work focuses on defining a quality measure and a validation protocol assessing IVUS motion compensation. On the grounds of continuum mechanics laws we introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases.  
  Address  
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  Publisher Springerlink Place of Publication Heidelberg Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-540-74271-5 Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GRR2007 Serial 1540  
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Author J. Elder; Fadi Dornaika; Y. Hou; R. Goldstein edit  openurl
  Title (up) Attentive wide-field sensing for visual telepresence and surveillance Type Book Chapter
  Year 2005 Publication L. Itti, G. Rees and J. Tsotsos (editors), Neurobiology of Attention, Academic Press / Elsevier Abbreviated Journal  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ EDH2005 Serial 604  
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Author Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez edit  openurl
  Title (up) Automatic Learning of Conceptual Knowledge for the Interpretation of Human Behavior in Video Sequences Type Book Chapter
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:507–514 Abbreviated Journal  
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  Address Girona (Spain)  
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  Notes ISE Approved no  
  Call Number ISE @ ise @ BFR2007 Serial 807  
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Author Jordina Torrents-Barrena; Aida Valls; Petia Radeva; Meritxell Arenas; Domenec Puig edit  doi
openurl 
  Title (up) Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis Type Book Chapter
  Year 2015 Publication Artificial Intelligence Research and Development Abbreviated Journal  
  Volume 277 Issue Pages 247 - 256  
  Keywords  
  Abstract Breast cancer disease has recently been classified into four subtypes regarding the molecular properties of the affected tumor region. For each patient, an accurate diagnosis of the specific type is vital to decide the most appropriate therapy in order to enhance life prospects. Nowadays, advanced therapeutic diagnosis research is focused on gene selection methods, which are not robust enough. Hence, we hypothesize that computer vision algorithms can offer benefits to address the problem of discriminating among them through X-Ray images. In this paper, we propose a novel approach driven by texture feature descriptors and machine learning techniques. First, we segment the tumour part through an active contour technique and then, we perform a complete fractal analysis to collect qualitative information of the region of interest in the feature extraction stage. Finally, several supervised and unsupervised classifiers are used to perform multiclass classification of the aforementioned data. The experimental results presented in this paper support that it is possible to establish a relation between each tumor subtype and the extracted features of the patterns revealed on mammograms.  
  Address  
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  Publisher IOS Press Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Frontiers in Artificial Intelligence and Applications Abbreviated Series Title  
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  Area Expedition Conference  
  Notes MILAB Approved no  
  Call Number Admin @ si @TVR2015 Serial 2780  
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Author Pau Baiget; Xavier Roca; Jordi Gonzalez edit  openurl
  Title (up) Autonomous Virtual Agents for Performance Evaluation of Tracking Algorithms Type Book Chapter
  Year 2008 Publication Articulated Motion and Deformable Objects, 5th International Conference AMDO 2008, Abbreviated Journal  
  Volume 5098 Issue Pages 299-308  
  Keywords  
  Abstract  
  Address Port d'Andratx (Mallorca)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ BRG2008 Serial 974  
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Author Joaquin Salas; P. Martinez; Jordi Gonzalez edit  openurl
  Title (up) Background Updating with the Use of Intrinsic Curves Type Book Chapter
  Year 2006 Publication International Conference on Image Analysis and Recognition (ICIAR´06), LNCS 4141 (A. Campilho et al., eds.), 1: 731–742, ISBN 978–3–540–44891–4 Abbreviated Journal  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number ISE @ ise @ SMG2006 Serial 768  
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