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Author Marta Teres; Eduard Vazquez edit  openurl
  Title Museums, spaces and museographical resources. Current state and proposals for a multidisciplinary framework to open new perspectives Type Conference Article
  Year 2010 Publication Proceedings of The CREATE 2010 Conference Abbreviated Journal  
  Volume Issue Pages 319–323  
  Keywords  
  Abstract Two of the main aims of a museum are to communicate its heritage and to make enjoy its visitors. This communication can be done through the pieces itself and the museographical resources but also through the building, the interior design, the light and the colour. Art museums, in opposition with other museums, lack on the application of these additional resources. Such a work necessarily requires a multidisciplinary point of view for a holistic vision of all what a museum implies and to use all its potential as a tool of knowledge and culture for all the visitors.  
  Address (up) Gjovik, Norway  
  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 CREATE  
  Notes Approved no  
  Call Number Admin @ si @ TeV2010 Serial 1298  
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Author Eduard Vazquez; Ramon Baldrich edit  openurl
  Title Non-supervised goodness measure for image segmentation Type Conference Article
  Year 2010 Publication Proceedings of The CREATE 2010 Conference Abbreviated Journal  
  Volume Issue Pages 334–335  
  Keywords  
  Abstract  
  Address (up) Gjovik, Norway  
  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 CREATE  
  Notes CIC Approved no  
  Call Number CAT @ cat @ VaB2010 Serial 1299  
Permanent link to this record
 

 
Author David Lloret; Antonio Lopez; Joan Serrat edit  openurl
  Title Precise registration of CT and MR volumes based on a new creaseness measure Type Miscellaneous
  Year 1998 Publication Workshop on Non–linear model–based image analysis (NMBIA’98). S. Marshall, N. Harvey and D. Shah Eds. Springer_Verlag London, pgs 15–20 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Glasgow (Scottland)  
  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 ADAS Approved no  
  Call Number ADAS @ adas @ LLS1998d Serial 487  
Permanent link to this record
 

 
Author David Lloret; Antonio Lopez; Joan Serrat edit  openurl
  Title 3-D image Processing and Modeling, workshop on non-linear model-based image analysis. Type Miscellaneous
  Year 1998 Publication NMBIA Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Glasgow, U.K.  
  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 ADAS Approved no  
  Call Number ADAS @ adas @ LLS1998c Serial 15  
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Author Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen edit   pdf
doi  openurl
  Title Tex-Nets: Binary Patterns Encoded Convolutional Neural Networks for Texture Recognition Type Conference Article
  Year 2017 Publication 19th International Conference on Multimodal Interaction Abbreviated Journal  
  Volume Issue Pages  
  Keywords Convolutional Neural Networks; Texture Recognition; Local Binary Paterns  
  Abstract Recognizing materials and textures in realistic imaging conditions is a challenging computer vision problem. For many years, local features based orderless representations were a dominant approach for texture recognition. Recently deep local features, extracted from the intermediate layers of a Convolutional Neural Network (CNN), are used as filter banks. These dense local descriptors from a deep model, when encoded with Fisher Vectors, have shown to provide excellent results for texture recognition. The CNN models, employed in such approaches, take RGB patches as input and train on a large amount of labeled images. We show that CNN models, which we call TEX-Nets, trained using mapped coded images with explicit texture information provide complementary information to the standard deep models trained on RGB patches. We further investigate two deep architectures, namely early and late fusion, to combine the texture and color information. Experiments on benchmark texture datasets clearly demonstrate that TEX-Nets provide complementary information to standard RGB deep network. Our approach provides a large gain of 4.8%, 3.5%, 2.6% and 4.1% respectively in accuracy on the DTD, KTH-TIPS-2a, KTH-TIPS-2b and Texture-10 datasets, compared to the standard RGB network of the same architecture. Further, our final combination leads to consistent improvements over the state-of-the-art on all four datasets.  
  Address (up) Glasgow; Scothland; November 2017  
  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 ACM  
  Notes LAMP; 600.109; 600.068; 600.120 Approved no  
  Call Number Admin @ si @ RKW2017 Serial 3038  
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Author M. Ivasic-Kos; M. Pobar; Jordi Gonzalez edit   pdf
doi  openurl
  Title Active Player Detection in Handball Videos Using Optical Flow and STIPs Based Measures Type Conference Article
  Year 2019 Publication 13th International Conference on Signal Processing and Communication Systems Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In handball videos recorded during the training, multiple players are present in the scene at the same time. Although they all might move and interact, not all players contribute to the currently relevant exercise nor practice the given handball techniques. The goal of this experiment is to automatically determine players on training footage that perform given handball techniques and are therefore considered active. It is a very challenging task for which a precise object detector is needed that can handle cluttered scenes with poor illumination, with many players present in different sizes and distances from the camera, partially occluded, moving fast. To determine which of the detected players are active, additional information is needed about the level of player activity. Since many handball actions are characterized by considerable changes in speed, position, and variations in the player's appearance, we propose using spatio-temporal interest points (STIPs) and optical flow (OF). Therefore, we propose an active player detection method combining the YOLO object detector and two activity measures based on STIPs and OF. The performance of the proposed method and activity measures are evaluated on a custom handball video dataset acquired during handball training lessons.  
  Address (up) Gold Coast; Australia; December 2019  
  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 ICSPCS2  
  Notes ISE; 600.098; 600.119 Approved no  
  Call Number Admin @ si @ IPG2019 Serial 3415  
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Author Jiaolong Xu; David Vazquez; Antonio Lopez; Javier Marin; Daniel Ponsa edit   pdf
doi  isbn
openurl 
  Title Learning a Multiview Part-based Model in Virtual World for Pedestrian Detection Type Conference Article
  Year 2013 Publication IEEE Intelligent Vehicles Symposium Abbreviated Journal  
  Volume Issue Pages 467 - 472  
  Keywords Pedestrian Detection; Virtual World; Part based  
  Abstract State-of-the-art deformable part-based models based on latent SVM have shown excellent results on human detection. In this paper, we propose to train a multiview deformable part-based model with automatically generated part examples from virtual-world data. The method is efficient as: (i) the part detectors are trained with precisely extracted virtual examples, thus no latent learning is needed, (ii) the multiview pedestrian detector enhances the performance of the pedestrian root model, (iii) a top-down approach is used for part detection which reduces the searching space. We evaluate our model on Daimler and Karlsruhe Pedestrian Benchmarks with publicly available Caltech pedestrian detection evaluation framework and the result outperforms the state-of-the-art latent SVM V4.0, on both average miss rate and speed (our detector is ten times faster).  
  Address (up) Gold Coast; Australia; June 2013  
  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 1931-0587 ISBN 978-1-4673-2754-1 Medium  
  Area Expedition Conference IV  
  Notes ADAS; 600.054; 600.057 Approved no  
  Call Number XVL2013; ADAS @ adas @ xvl2013a Serial 2214  
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Author Lasse Martensson; Anders Hast; Alicia Fornes edit   pdf
isbn  openurl
  Title Word Spotting as a Tool for Scribal Attribution Type Conference Article
  Year 2017 Publication 2nd Conference of the association of Digital Humanities in the Nordic Countries Abbreviated Journal  
  Volume Issue Pages 87-89  
  Keywords  
  Abstract  
  Address (up) Gothenburg; Suecia; March 2017  
  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 978-91-88348-83-8 Medium  
  Area Expedition Conference DHN  
  Notes DAG; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ MHF2017 Serial 2954  
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Author Martha Mackay; Fernando Alonso; Pere Salamero; Xavier Baro; Jordi Gonzalez; Sergio Escalera edit   pdf
openurl 
  Title Care and caring: future proofing the new demographics Type Conference Article
  Year 2015 Publication 6th International Carers Conference Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract With an ageing population, the issue of care provision is becoming increasingly important. The simple aspiration of the majority of older people is to live safely and well at home. Housing will be part of health & care integration in the following years and decades. A higher proportion of people will have to rely on informal care through family, friends, neighbors and others who
provide care to an older person in need of assistance (around 80% of care across the EU). They do not usually have a formal status and are usually unpaid. We need to ensure that all disabled or chronically ill people can get the help they need without overburdening their families.
The physical and emotional stress of carers is one of the dangers that this dependency can bring. To prevent carers burnout it is necessary to provide new solutions that are affordable and user friendly for the families and caregivers.
 
  Address (up) Gothenburg; Sweden; September 2015  
  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 CARERS  
  Notes HuPBA; ISE; 600.078;MV Approved no  
  Call Number Admin @ si @ MAS2015b Serial 2678  
Permanent link to this record
 

 
Author Oriol Pujol; Petia Radeva; Jordi Vitria edit  openurl
  Title Traffic sign recognition using an adaptive boosting multiclass framework Type Miscellaneous
  Year 2005 Publication Workshop sobre Reconocimiento de Formas y Analisis de Imagenes (AERFAI), I Congreso Español de Informatica (CEDI´2005) Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Granada (Spain)  
  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;MILAB;HuPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ PRV2005 Serial 618  
Permanent link to this record
 

 
Author David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin edit   pdf
openurl 
  Title Cool world: domain adaptation of virtual and real worlds for human detection using active learning Type Conference Article
  Year 2011 Publication NIPS Domain Adaptation Workshop: Theory and Application Abbreviated Journal NIPS-DA  
  Volume Issue Pages  
  Keywords Pedestrian Detection; Virtual; Domain Adaptation; Active Learning  
  Abstract Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity.  
  Address (up) Granada, Spain  
  Corporate Author Thesis  
  Publisher Place of Publication Granada, Spain Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DA-NIPS  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ VLP2011b Serial 1756  
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Author J. Mauri; E Fernandez-Nofrerias; E. Esplugas; A. Cequier; David Rotger; Ricardo Toledo; Petia Radeva; ; Juan J. Villanueva edit  openurl
  Title Ecografia Intracoronaria: Navegacion Informatica por el cubo de datos de las imagenes. Type Miscellaneous
  Year 2000 Publication Congreso de la Sociedad Española de Cardiologia. Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Granada.  
  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 MILAB;ADAS Approved no  
  Call Number BCNPCL @ bcnpcl @ MNE2000 Serial 356  
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Author Md. Mostafa Kamal Sarker; Hatem A. Rashwan; Farhan Akram; Syeda Furruka Banu; Adel Saleh; Vivek Kumar Singh; Forhad U. H. Chowdhury; Saddam Abdulwahab; Santiago Romani; Petia Radeva; Domenec Puig edit   pdf
url  openurl
  Title SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks. Type Conference Article
  Year 2018 Publication 21st International Conference on Medical Image Computing & Computer Assisted Intervention Abbreviated Journal  
  Volume 2 Issue Pages 21-29  
  Keywords  
  Abstract Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma. In this paper, we present a robust deep learning SLS model, so-called SLSDeep, which is represented as an encoder-decoder network. The encoder network is constructed by dilated residual layers, in turn, a pyramid pooling network followed by three convolution layers is used for the decoder. Unlike the traditional methods employing a cross-entropy loss, we investigated a loss function by combining both Negative Log Likelihood (NLL) and End Point Error (EPE) to accurately segment the melanoma regions with sharp boundaries. The robustness of the proposed model was evaluated on two public databases: ISBI 2016 and 2017 for skin lesion analysis towards melanoma detection challenge. The proposed model outperforms the state-of-the-art methods in terms of segmentation accuracy. Moreover, it is capable to segment more than 100 images of size 384x384 per second on a recent GPU.  
  Address (up) Granada; Espanya; September 2018  
  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 MICCAI  
  Notes MILAB; no proj Approved no  
  Call Number Admin @ si @ SRA2018 Serial 3112  
Permanent link to this record
 

 
Author Esmitt Ramirez; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil edit   pdf
url  openurl
  Title Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy Type Conference Article
  Year 2018 Publication OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis Abbreviated Journal  
  Volume 11041 Issue Pages  
  Keywords Biopsy guiding; Bronchoscopy; Lung biopsy; Intervention guiding; Airway codification  
  Abstract Bronchoscopy examinations allow biopsy of pulmonary nodules with minimum risk for the patient. Even for experienced bronchoscopists, it is difficult to guide the bronchoscope to most distal lesions and obtain an accurate diagnosis. This paper presents an image-based codification of the bronchial anatomy for bronchoscopy biopsy guiding. The 3D anatomy of each patient is codified as a binary tree with nodes representing bronchial levels and edges labeled using their position on images projecting the 3D anatomy from a set of branching points. The paths from the root to leaves provide a codification of navigation routes with spatially consistent labels according to the anatomy observes in video bronchoscopy explorations. We evaluate our labeling approach as a guiding system in terms of the number of bronchial levels correctly codified, also in the number of labels-based instructions correctly supplied, using generalized mixed models and computer-generated data. Results obtained for three independent observers prove the consistency and reproducibility of our guiding system. We trust that our codification based on viewer’s projection might be used as a foundation for the navigation process in Virtual Bronchoscopy systems.  
  Address (up) Granada; September 2018  
  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 MICCAIW  
  Notes IAM; 600.096; 600.075; 601.323; 600.145 Approved no  
  Call Number Admin @ si @ RSB2018b Serial 3137  
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Author Sonia Baeza; Debora Gil; Carles Sanchez; Guillermo Torres; Ignasi Garcia Olive; Ignasi Guasch; Samuel Garcia Reina; Felipe Andreo; Jose Luis Mate; Jose Luis Vercher; Antonio Rosell edit  openurl
  Title Biopsia virtual radiomica para el diagnóstico histológico de nódulos pulmonares – Resultados intermedios del proyecto Radiolung Type Conference Article
  Year 2023 Publication SEPAR Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Pòster  
  Address (up) Granada; Spain; June 2023  
  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 SEPAR  
  Notes IAM Approved no  
  Call Number Admin @ si @ BGS2023 Serial 3951  
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