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Author |
Maya Dimitrova; Ch. Roumenin; Siya Lozanova; David Rotger; Petia Radeva |
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Title  |
An Interface System Based on Multimodal Principle for Cardiological Diagnosis Assistance |
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Conference Article |
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2007 |
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International Conference On Computer Systems And Technologies |
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IIIB.4 |
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1–6 |
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Bulgaria |
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CompSysTech’07 |
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MILAB |
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BCNPCL @ bcnpcl @ DRL2007 |
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833 |
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Author |
Jaume Garcia; Joel Barajas; Francesc Carreras; Sandra Pujades; Petia Radeva |
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Title |
An intuitive validation technique to compare local versus global tagged MRI analysis |
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Conference Article |
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Year |
2005 |
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Computers In Cardiology |
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32 |
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29–32 |
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Myocardium appears as a uniform tissue that seen in convectional Magnetic Resonance Images (MRI) shows just the contractile part of its movement. MR Tagging is a unique imaging technique that prints a grid over the tissue which moves according to the underlying movement of the myocardium revealing the true deformation of the cardiac muscle. Optical flow techniques based on spectral information estimate tissue displacement by analyzing information encoded in the phase maps which can be obtained using, local (Gabor) and global (HARP) methods. In this paper we compare both in synthetic and real Tagged MR sequences. We conclude that local method is slightly more accurate than the global one. On the other hand, global method is more efficient as it is much faster and less parameters have to be taken into account |
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Lyon (France) |
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0-7803-9337-6 |
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IAM;MILAB |
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IAM @ iam @ GBC2005 |
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639 |
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Author |
Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco |
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Title |
An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction |
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Conference Article |
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2012 |
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2nd Joint AVA / BMVA Meeting on Biological and Machine Vision |
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Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM).
This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here. |
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AV A |
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CIC |
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Admin @ si @ OPD2012a |
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2132 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An Iterative Multiresolution Scheme for SFM |
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Conference Article |
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Year |
2006 |
Publication |
International Conference on Image Analysis and Recognition |
Abbreviated Journal |
ICIAR 2006 |
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LNCS 4141 |
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1 |
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804–815 |
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ADAS |
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ADAS @ adas @ JSL2006c |
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704 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An iterative multiresolution scheme for SFM with missing data |
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Journal Article |
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Year |
2009 |
Publication |
Journal of Mathematical Imaging and Vision |
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JMIV |
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Volume |
34 |
Issue |
3 |
Pages |
240–258 |
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Abstract |
Several techniques have been proposed for tackling the Structure from Motion problem through factorization in the case of missing data. However, when the percentage of unknown data is high, most of them may not perform as well as expected. Focussing on this problem, an iterative multiresolution scheme, which aims at recovering missing entries in the originally given input matrix, is proposed. Information recovered following a coarse-to-fine strategy is used for filling in the missing entries. The objective is to recover, as much as possible, missing data in the given matrix.
Thus, when a factorization technique is applied to the partially or totally filled in matrix, instead of to the originally given input one, better results will be obtained. An evaluation study about the robustness to missing and noisy data is reported.
Experimental results obtained with synthetic and real video sequences are presented to show the viability of the proposed approach. |
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ADAS |
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ADAS @ adas @ JSL2009a |
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1163 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An Iterative Multiresolution Scheme for SFM with Missing Data: single and multiple object scenes |
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Journal Article |
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Year |
2010 |
Publication |
Image and Vision Computing |
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IMAVIS |
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28 |
Issue |
1 |
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164-176 |
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Most of the techniques proposed for tackling the Structure from Motion problem (SFM) cannot deal with high percentages of missing data in the matrix of trajectories. Furthermore, an additional problem should be faced up when working with multiple object scenes: the rank of the matrix of trajectories should be estimated. This paper presents an iterative multiresolution scheme for SFM with missing data to be used in both the single and multiple object cases. The proposed scheme aims at recovering missing entries in the original input matrix. The objective is to improve the results by applying a factorization technique to the partially or totally filled in matrix instead of to the original input one. Experimental results obtained with synthetic and real data sequences, containing single and multiple objects, are presented to show the viability of the proposed approach. |
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0262-8856 |
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ADAS |
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ADAS @ adas @ JSL2010 |
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1278 |
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Author |
Dimosthenis Karatzas; Sergi Robles; Lluis Gomez |
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Title |
An on-line platform for ground truthing and performance evaluation of text extraction systems |
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Conference Article |
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Year |
2014 |
Publication |
11th IAPR International Workshop on Document Analysis and Systems |
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242 - 246 |
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This paper presents a set of on-line software tools for creating ground truth and calculating performance evaluation metrics for text extraction tasks such as localization, segmentation and recognition. The platform supports the definition of comprehensive ground truth information at different text representation levels while it offers centralised management and quality control of the ground truthing effort. It implements a range of state of the art performance evaluation algorithms and offers functionality for the definition of evaluation scenarios, on-line calculation of various performance metrics and visualisation of the results. The
presented platform, which comprises the backbone of the ICDAR 2011 (challenge 1) and 2013 (challenges 1 and 2) Robust Reading competitions, is now made available for public use. |
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Tours; Francia; April 2014 |
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978-1-4799-3243-6 |
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DAS |
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DAG; 600.056; 600.077 |
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Admin @ si @ KRG2014 |
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2491 |
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Author |
Joost Van de Weijer; Fahad Shahbaz Khan |
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Title |
An Overview of Color Name Applications in Computer Vision |
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2015 |
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Computational Color Imaging Workshop |
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color features; color names; object recognition |
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In this article we provide an overview of color name applications in computer vision. Color names are linguistic labels which humans use to communicate color. Computational color naming learns a mapping from pixels values to color names. In recent years color names have been applied to a wide variety of computer vision applications, including image classification, object recognition, texture classification, visual tracking and action recognition. Here we provide an overview of these results which show that in general color names outperform photometric invariants as a color representation. |
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Saint Etienne; France; March 2015 |
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CCIW |
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LAMP; 600.079; 600.068 |
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Admin @ si @ WeK2015 |
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2586 |
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Author |
Katerine Diaz; Francesc J. Ferri; Aura Hernandez-Sabate |
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An overview of incremental feature extraction methods based on linear subspaces |
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Journal Article |
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2018 |
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Knowledge-Based Systems |
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KBS |
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145 |
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219-235 |
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With the massive explosion of machine learning in our day-to-day life, incremental and adaptive learning has become a major topic, crucial to keep up-to-date and improve classification models and their corresponding feature extraction processes. This paper presents a categorized overview of incremental feature extraction based on linear subspace methods which aim at incorporating new information to the already acquired knowledge without accessing previous data. Specifically, this paper focuses on those linear dimensionality reduction methods with orthogonal matrix constraints based on global loss function, due to the extensive use of their batch approaches versus other linear alternatives. Thus, we cover the approaches derived from Principal Components Analysis, Linear Discriminative Analysis and Discriminative Common Vector methods. For each basic method, its incremental approaches are differentiated according to the subspace model and matrix decomposition involved in the updating process. Besides this categorization, several updating strategies are distinguished according to the amount of data used to update and to the fact of considering a static or dynamic number of classes. Moreover, the specific role of the size/dimension ratio in each method is considered. Finally, computational complexity, experimental setup and the accuracy rates according to published results are compiled and analyzed, and an empirical evaluation is done to compare the best approach of each kind. |
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0950-7051 |
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ADAS; 600.118 |
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Admin @ si @ DFH2018 |
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3090 |
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Author |
Salvatore Tabbone; Oriol Ramos Terrades |
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Title |
An Overview of Symbol Recognition |
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Book Chapter |
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2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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D |
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523-551 |
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Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting |
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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. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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Admin @ si @ TaT2014 |
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2489 |
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Qingshan Chen; Zhenzhen Quan; Yujun Li; Chao Zhai; Mikhail Mozerov |
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Title |
An Unsupervised Domain Adaption Approach for Cross-Modality RGB-Infrared Person Re-Identification |
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Journal Article |
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2023 |
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IEEE Sensors Journal |
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IEEE-SENS |
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23 |
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24 |
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Q. Chen, Z. Quan, Y. Li, C. Zhai and M. G. Mozerov |
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Dual-camera systems commonly employed in surveillance serve as the foundation for RGB-infrared (IR) cross-modality person re-identification (ReID). However, significant modality differences give rise to inferior performance compared to single-modality scenarios. Furthermore, most existing studies in this area rely on supervised training with meticulously labeled datasets. Labeling RGB-IR image pairs is more complex than labeling conventional image data, and deploying pretrained models on unlabeled datasets can lead to catastrophic performance degradation. In contrast to previous solutions that focus solely on cross-modality or domain adaptation issues, this article presents an end-to-end unsupervised domain adaptation (UDA) framework for the cross-modality person ReID, which can simultaneously address both of these challenges. This model employs source domain classes, target domain clusters, and unclustered instance samples for the training, maximizing the comprehensive use of the dataset. Moreover, it addresses the problem of mismatched clustering labels between the two modalities in the target domain by incorporating a label matching module that reassigns reliable clusters with labels, ensuring correspondence between different modality labels. We construct the loss function by incorporating distinctiveness loss and multiplicity loss, both of which are determined by the similarity of neighboring features in the predicted feature space and the difference between distant features. This approach enables efficient feature clustering and cluster class assignment to occur concurrently. Eight UDA cross-modality person ReID experiments are conducted on three real datasets and six synthetic datasets. The experimental results unequivocally demonstrate that the proposed model outperforms the existing state-of-the-art algorithms to a significant degree. Notably, in RegDB → RegDB_light, the Rank-1 accuracy exhibits a remarkable improvement of 8.24%. |
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LAMP |
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Admin @ si @ CQL2023 |
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3884 |
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Author |
Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera |
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Analisis de la Expresion Oral y Gestual en Proyectos Fin de Carrera Via un Sistema de Vision Artificial |
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Miscellaneous |
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2011 |
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Revista electronica de la asociacion de enseñantes universitarios de la informatica AENUI |
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ReVision |
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4 |
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1 |
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8-18 |
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La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación. |
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1989-1199 |
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MILAB;HuPBA;MV |
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Admin @ si @ PGB2011c |
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1783 |
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O. Rodriguez; J. Mauri; E Fernandez-Nofrerias; A. Tovar; R. Villuendas; V. Valle; Oriol Pujol; Petia Radeva |
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Analisis de texturas mediante la modificacion de un modelo binario local para la segmentacion automatica de secuencias de ecografia intracoronaria |
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2003 |
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Revista Española de Cardiologia (IF: 0.959), 56(2), Congreso de las Enfermedades Cardiovasculares |
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Sevilla (Spain) |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ RMF2003f |
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413 |
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Author |
Oriol Rodriguez-Leor; Debora Gil; Eduard Fernandez-Nofrerias |
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Title |
Analisis en los cambios en el nivel de gris en las secuencias angiograficas mediante descriptores estadisticos para determinar la perfusion miocardica |
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2006 |
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Revista Española de Cardiología |
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REC |
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59 Supl 2-166 |
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2 |
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128 |
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IAM; |
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no |
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IAM @ iam @ RGF2006 |
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1640 |
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Author |
A. Pagani |
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Title |
Analisis y comparacion de metodos para la caracterizacion de la respuesta espectral de camaras |
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Report |
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2002 |
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CVC Technical Report # 64 |
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no |
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Admin @ si @ Pag2002 |
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330 |
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