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Author (down) Mariano Vazquez; Ruth Aris; Guillaume Hozeaux; R.Aubry; P.Villar;Jaume Garcia ; Debora Gil; Francesc Carreras edit   pdf
url  doi
openurl 
  Title A massively parallel computational electrophysiology model of the heart Type Journal Article
  Year 2011 Publication International Journal for Numerical Methods in Biomedical Engineering Abbreviated Journal IJNMBE  
  Volume 27 Issue Pages 1911-1929  
  Keywords computational electrophysiology; parallelization; finite element methods  
  Abstract This paper presents a patient-sensitive simulation strategy capable of using the most efficient way the high-performance computational resources. The proposed strategy directly involves three different players: Computational Mechanics Scientists (CMS), Image Processing Scientists and Cardiologists, each one mastering its own expertise area within the project. This paper describes the general integrative scheme but focusing on the CMS side presents a massively parallel implementation of computational electrophysiology applied to cardiac tissue simulation. The paper covers different angles of the computational problem: equations, numerical issues, the algorithm and parallel implementation. The proposed methodology is illustrated with numerical simulations testing all the different possibilities, ranging from small domains up to very large ones. A key issue is the almost ideal scalability not only for large and complex problems but also for medium-size meshes. The explicit formulation is particularly well suited for solving this highly transient problems, with very short time-scale.  
  Address Swansea (UK)  
  Corporate Author John Wiley & Sons, Ltd. Thesis  
  Publisher John Wiley & Sons, Ltd. 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 IAM Approved no  
  Call Number IAM @ iam @ VAH2011 Serial 1198  
Permanent link to this record
 

 
Author (down) Maria Vanrell; Ramon Baldrich; Anna Salvatella; Robert Benavente; Francesc Tous edit  openurl
  Title Induction operators for a computational colour-texture representation Type Journal
  Year 2004 Publication Computer Vision and Image Understanding, 94(1–3):92–114, ISSN: 1077–3142 (IF: 0.651) Abbreviated Journal  
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  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number CAT @ cat @ VBS2004 Serial 453  
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Author (down) Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich edit   pdf
url  isbn
openurl 
  Title Perception Based Representations for Computational Colour Type Conference Article
  Year 2011 Publication 3rd International Workshop on Computational Color Imaging Abbreviated Journal  
  Volume 6626 Issue Pages 16-30  
  Keywords colour perception, induction, naming, psychophysical data, saliency, segmentation  
  Abstract The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.  
  Address Milan, Italy  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor Raimondo Schettini, Shoji Tominaga, Alain Trémeau  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-20403-6 Medium  
  Area Expedition Conference CCIW  
  Notes CIC Approved no  
  Call Number Admin @ si @ VMB2011 Serial 1733  
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Author (down) Maria Vanrell; Jordi Vitria; Xavier Roca edit  openurl
  Title A multidimensional scaling approach to explore the behavior of a texture perception algorithm. Type Journal Article
  Year 1997 Publication Machine Vision and Applications Abbreviated Journal  
  Volume 9 Issue Pages 262–271  
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  Area Expedition Conference  
  Notes OR;ISE;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VVR1997 Serial 35  
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Author (down) Maria Vanrell; Jordi Vitria; Xavier Roca edit  openurl
  Title A General Morphological Framework for Perceptual Texture Discrimination based on Granulometries. Type Miscellaneous
  Year 1993 Publication Technical Workshop on Mathematical Morphology and its Applications to Signal Processing. Abbreviated Journal  
  Volume Issue Pages  
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  Address Barcelona  
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  Area Expedition Conference  
  Notes OR;ISE;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VVR1993 Serial 154  
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Author (down) Maria Vanrell; Jordi Vitria edit  openurl
  Title Mathematical Morphology, Granulometries and Texture Perception. Type Miscellaneous
  Year 1993 Publication SPIE International Symposium on Optical Instrumentation and Applied Science (Conference on image Algebra and Morphological image Processing IV). Abbreviated Journal  
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  Address San Diego; CA; USA  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VaV1993 Serial 178  
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Author (down) Maria Vanrell; Jordi Vitria edit  openurl
  Title Optimal 3x3 decomposable disks for morphological transformations Type Journal
  Year 1997 Publication Image and Vision Computing, 15(2): 845–854 Abbreviated Journal  
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  Area Expedition Conference  
  Notes OR;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VaV1997c Serial 543  
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Author (down) Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva edit  openurl
  Title Colour Normalisation Based on Background Information. Type Miscellaneous
  Year 2001 Publication Proceeding ICIP 2001, IEEE International Conference on Image Processing Abbreviated Journal ICIP 2001  
  Volume Issue 1 Pages 874–877  
  Keywords  
  Abstract  
  Address Grecia.  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS;DAG;CIC Approved no  
  Call Number ADAS @ adas @ VLP2001 Serial 167  
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Author (down) Maria Vanrell edit  openurl
  Title Exploring the space of behaviour of a texture perception algorithm Type Report
  Year 1997 Publication CVC Technical Report #12 Abbreviated Journal  
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  Address CVC (UAB)  
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  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number CAT @ cat @ Van1997 Serial 523  
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Author (down) Maria Salamo; Sergio Escalera; Petia Radeva edit  doi
isbn  openurl
  Title Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender Type Conference Article
  Year 2009 Publication 8th International Conference on Case-Based Reasoning Abbreviated Journal  
  Volume 5650 Issue Pages 298–312  
  Keywords  
  Abstract Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help users to navigate through product spaces, alternatively making product suggestions and eliciting users feedback. Critiquing is a common form of feedback and incremental critiquing-based recommender system has shown its efficiency to personalize products based primarily on a quality measure. This quality measure influences the recommendation process and it is obtained by the combination of compatibility and similarity scores. In this paper, we describe new compatibility strategies whose basis is on reinforcement learning and a new feature weighting technique which is based on the user’s history of critiques. Moreover, we show that our methodology can significantly improve recommendation efficiency in comparison with the state-of-the-art approaches.  
  Address Seattle, USA  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02998-1 Medium  
  Area Expedition Conference ICCBR  
  Notes HuPBA; MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SER2009 Serial 1187  
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Author (down) Maria Salamo; Sergio Escalera edit  openurl
  Title Increasing Retrieval Quality in Conversational Recommenders Type Journal Article
  Year 2011 Publication IEEE Transactions on Knowledge and Data Engineering Abbreviated Journal TKDE  
  Volume 99 Issue Pages 1-1  
  Keywords  
  Abstract IF JCR CCIA 2.286 2009 24/103
JCR Impact Factor 2010: 1.851
A major task of research in conversational recommender systems is personalization. Critiquing is a common and powerful form of feedback, where a user can express her feature preferences by applying a series of directional critiques over the recommendations instead of providing specific preference values. Incremental Critiquing is a conversational recommender system that uses critiquing as a feedback to efficiently personalize products. The expectation is that in each cycle the system retrieves the products that best satisfy the user’s soft product preferences from a minimal information input. In this paper, we present a novel technique that increases retrieval quality based on a combination of compatibility and similarity scores. Under the hypothesis that a user learns Turing the recommendation process, we propose two novel exponential reinforcement learning approaches for compatibility that take into account both the instant at which the user makes a critique and the number of satisfied critiques. Moreover, we consider that the impact of features on the similarity differs according to the preferences manifested by the user. We propose a global weighting approach that uses a common weight for nearest cases in order to focus on groups of relevant products. We show that our methodology significantly improves recommendation efficiency in four data sets of different sizes in terms of session length in comparison with state-of-the-art approaches. Moreover, our recommender shows higher robustness against noisy user data when compared to classical approaches
 
  Address  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1041-4347 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; HuPBA Approved no  
  Call Number Admin @ si @ SaE2011 Serial 1713  
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Author (down) Maria Salamo; Inmaculada Rodriguez; Maite Lopez; Anna Puig; Simone Balocco; Mariona Taule edit  openurl
  Title Recurso docente para la atención de la diversidad en el aula mediante la predicción de notas Type Journal
  Year 2016 Publication ReVision Abbreviated Journal  
  Volume 9 Issue 1 Pages  
  Keywords Aprendizaje automatico; Sistema de prediccion de notas; Herramienta docente  
  Abstract Desde la implantación del Espacio Europeo de Educación Superior (EEES) en los diferentes grados, se ha puesto de manifiesto la necesidad de utilizar diversos mecanismos que permitan tratar la diversidad en el aula, evaluando automáticamente y proporcionando una retroalimentación rápida tanto al alumnado como al profesorado sobre la evolución de los alumnos en una asignatura. En este artículo se presenta la evaluación de la exactitud en las predicciones de GRADEFORESEER, un recurso docente para la predicción de notas basado en técnicas de aprendizaje automático que permite evaluar la evolución del alumnado y estimar su nota final al terminar el curso. Este recurso se ha complementado con una interfaz de usuario para el profesorado que puede ser usada en diferentes plataformas software (sistemas operativos) y en cualquier asignatura de un grado en la que se utilice evaluación continuada. Además de la descripción del recurso, este artículo presenta los resultados obtenidos al aplicar el sistema de predicción en cuatro asignaturas de disciplinas distintas: Programación I (PI), Diseño de Software (DSW) del grado de Ingeniería Informática, Tecnologías de la Información y la Comunicación (TIC) del grado de Lingüística y la asignatura Fundamentos de Tecnología (FDT) del grado de Información y Documentación, todas ellas impartidas en la Universidad de Barcelona.

La capacidad predictiva se ha evaluado de forma binaria (aprueba o no) y según un criterio de rango (suspenso, aprobado, notable o sobresaliente), obteniendo mejores predicciones en los resultados evaluados de forma binaria.
 
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; Approved no  
  Call Number Admin @ si @ SRL2016 Serial 2820  
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Author (down) Maria Oliver; Gloria Haro; Mariella Dimiccoli; Baptiste Mazin; Coloma Ballester edit   pdf
openurl 
  Title A computational model of amodal completion Type Conference Article
  Year 2016 Publication SIAM Conference on Imaging Science Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This paper presents a computational model to recover the most likely interpretation of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler's elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler's elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling.  
  Address Albuquerque; New Mexico; USA; May 2016  
  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 IS  
  Notes MILAB; 601.235 Approved no  
  Call Number Admin @ si @OHD2016a Serial 2788  
Permanent link to this record
 

 
Author (down) Maria Ines Torres; Javier Mikel Olaso; Cesar Montenegro; Riberto Santana; A.Vazquez; Raquel Justo; J.A.Lozano; Stephan Schogl; Gerard Chollet; Nazim Dugan; M.Irvine; N.Glackin; C.Pickard; Anna Esposito; Gennaro Cordasco; Alda Troncone; Dijana Petrovska Delacretaz; Aymen Mtibaa; Mohamed Amine Hmani; M.S.Korsnes; L.J.Martinussen; Sergio Escalera; C.Palmero Cantariño; Olivier Deroo; O.Gordeeva; Jofre Tenorio Laranga; E.Gonzalez Fraile; Begoña Fernandez Ruanova; A.Gonzalez Pinto edit   pdf
url  openurl
  Title The EMPATHIC project: mid-term achievements Type Conference Article
  Year 2019 Publication 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments Abbreviated Journal  
  Volume Issue Pages 629-638  
  Keywords  
  Abstract Maria Ines Torres; Javier Mikel Olaso, César Montenegro, Riberto Santana, A. Vázquez, Raquel Justo, J. A. Lozano, Stephan Schlögl, Gérard Chollet, Nazim Dugan, M. Irvine, N. Glackin, C. Pickard, Anna Esposito, Gennaro Cordasco, Alda Troncone, Dijana Petrovska-Delacrétaz, Aymen Mtibaa, Mohamed Amine Hmani, M. S. Korsnes, L. J. Martinussen, Sergio Escalera, C. Palmero Cantariño, Olivier Deroo, O. Gordeeva, Jofre Tenorio-Laranga, E. Gonzalez-Fraile, Begoña Fernández-Ruanova, A. Gonzalez-Pinto  
  Address Rhodes Greece; June 2019  
  Corporate Author Thesis  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference PETRA  
  Notes HUPBA; no proj Approved no  
  Call Number Admin @ si @ TOM2019 Serial 3325  
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Author (down) Maria Elena Meza-de-Luna; Juan Ramon Terven Salinas; Bogdan Raducanu; Joaquin Salas edit   pdf
doi  openurl
  Title Assessing the Influence of Mirroring on the Perception of Professional Competence using Wearable Technology Type Journal Article
  Year 2016 Publication IEEE Transactions on Affective Computing Abbreviated Journal TAC  
  Volume 9 Issue 2 Pages 161-175  
  Keywords Mirroring; Nodding; Competence; Perception; Wearable Technology  
  Abstract Nonverbal communication is an intrinsic part in daily face-to-face meetings. A frequently observed behavior during social interactions is mirroring, in which one person tends to mimic the attitude of the counterpart. This paper shows that a computer vision system could be used to predict the perception of competence in dyadic interactions through the automatic detection of mirroring
events. To prove our hypothesis, we developed: (1) A social assistant for mirroring detection, using a wearable device which includes a video camera and (2) an automatic classifier for the perception of competence, using the number of nodding gestures and mirroring events as predictors. For our study, we used a mixed-method approach in an experimental design where 48 participants acting as customers interacted with a confederated psychologist. We found that the number of nods or mirroring events has a significant influence on the perception of competence. Our results suggest that: (1) Customer mirroring is a better predictor than psychologist mirroring; (2) the number of psychologist’s nods is a better predictor than the number of customer’s nods; (3) except for the psychologist mirroring, the computer vision algorithm we used worked about equally well whether it was acquiring images from wearable smartglasses or fixed cameras.
 
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  Notes OR; 600.072;MV Approved no  
  Call Number Admin @ si @ MTR2016 Serial 2826  
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