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Author G. Zahnd; Simone Balocco; A. Serusclat; P. Moulin; M. Orkisz; D. Vray edit  doi
openurl 
  Title Progressive attenuation of the longitudinal kinetics in the common carotid artery: preliminary in vivo assessment Ultrasound in Medicine and Biology Type Journal Article
  Year 2015 Publication Ultrasound in Medicine and Biology Abbreviated Journal UMB  
  Volume 41 Issue 1 Pages 339-345  
  Keywords (down) Arterial stiffness; Atherosclerosis; Common carotid artery; Longitudinal kinetics; Motion tracking; Ultrasound imaging  
  Abstract Longitudinal kinetics (LOKI) of the arterial wall consists of the shearing motion of the intima-media complex over the adventitia layer in the direction parallel to the blood flow during the cardiac cycle. The aim of this study was to investigate the local variability of LOKI amplitude along the length of the vessel. By use of a previously validated motion-estimation framework, 35 in vivo longitudinal B-mode ultrasound cine loops of healthy common carotid arteries were analyzed. Results indicated that LOKI amplitude is progressively attenuated along the length of the artery, as it is larger in regions located on the proximal side of the image (i.e., toward the heart) and smaller in regions located on the distal side of the image (i.e., toward the head), with an average attenuation coefficient of -2.5 ± 2.0%/mm. Reported for the first time in this study, this phenomenon is likely to be of great importance in improving understanding of atherosclerosis mechanisms, and has the potential to be a novel index of arterial stiffness.  
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  Notes MILAB Approved no  
  Call Number Admin @ si @ ZBS2014 Serial 2556  
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Author 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 (down) 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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  Notes MILAB; Approved no  
  Call Number Admin @ si @ SRL2016 Serial 2820  
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Author Meysam Madadi; Sergio Escalera; Jordi Gonzalez; Xavier Roca; Felipe Lumbreras edit  doi
openurl 
  Title Multi-part body segmentation based on depth maps for soft biometry analysis Type Journal Article
  Year 2015 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 56 Issue Pages 14-21  
  Keywords (down) 3D shape context; 3D point cloud alignment; Depth maps; Human body segmentation; Soft biometry analysis  
  Abstract This paper presents a novel method extracting biometric measures using depth sensors. Given a multi-part labeled training data, a new subject is aligned to the best model of the dataset, and soft biometrics such as lengths or circumference sizes of limbs and body are computed. The process is performed by training relevant pose clusters, defining a representative model, and fitting a 3D shape context descriptor within an iterative matching procedure. We show robust measures by applying orthogonal plates to body hull. We test our approach in a novel full-body RGB-Depth data set, showing accurate estimation of soft biometrics and better segmentation accuracy in comparison with random forest approach without requiring large training data.  
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  Notes HuPBA; ISE; ADAS; 600.076;600.049; 600.063; 600.054; 302.018;MILAB Approved no  
  Call Number Admin @ si @ MEG2015 Serial 2588  
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Author Petia Radeva; J. Martinez; A. Tovar; X. Binefa; Jordi Vitria; Juan J. Villanueva edit  openurl
  Title CORKIDENT: an automatic vision system for real-time inspection of natural products. Type Journal Article
  Year 1999 Publication Abbreviated Journal  
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  Address Wales  
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  Notes OR;MILAB;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RMT1999 Serial 23  
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Author Jordi Vitria; Petia Radeva; X. Binefa edit  openurl
  Title EigenHistograms: using low dimensional models of color distribution for real time object recognition Type Journal Article
  Year 1999 Publication Abbreviated Journal  
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  Address Ljubliana, Slovenia, Springer-Verlag  
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  Notes OR;MILAB;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VRB1999a Serial 29  
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