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Author Parichehr Behjati Ardakani; Pau Rodriguez; Armin Mehri; Isabelle Hupont; Carles Fernandez; Jordi Gonzalez edit   pdf
doi  openurl
  Title (up) OverNet: Lightweight Multi-Scale Super-Resolution with Overscaling Network Type Conference Article
  Year 2021 Publication IEEE Winter Conference on Applications of Computer Vision Abbreviated Journal  
  Volume Issue Pages 2693-2702  
  Keywords  
  Abstract Super-resolution (SR) has achieved great success due to the development of deep convolutional neural networks (CNNs). However, as the depth and width of the networks increase, CNN-based SR methods have been faced with the challenge of computational complexity in practice. More- over, most SR methods train a dedicated model for each target resolution, losing generality and increasing memory requirements. To address these limitations we introduce OverNet, a deep but lightweight convolutional network to solve SISR at arbitrary scale factors with a single model. We make the following contributions: first, we introduce a lightweight feature extractor that enforces efficient reuse of information through a novel recursive structure of skip and dense connections. Second, to maximize the performance of the feature extractor, we propose a model agnostic reconstruction module that generates accurate high-resolution images from overscaled feature maps obtained from any SR architecture. Third, we introduce a multi-scale loss function to achieve generalization across scales. Experiments show that our proposal outperforms previous state-of-the-art approaches in standard benchmarks, while maintaining relatively low computation and memory requirements.  
  Address Virtual; January 2021  
  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 WACV  
  Notes ISE; 600.119; 600.098 Approved no  
  Call Number Admin @ si @ BRM2021 Serial 3512  
Permanent link to this record
 

 
Author Stepan Simsa; Michal Uricar; Milan Sulc; Yash Patel; Ahmed Hamdi; Matej Kocian; Matyas Skalicky; Jiri Matas; Antoine Doucet; Mickael Coustaty; Dimosthenis Karatzas edit  url
doi  openurl
  Title (up) Overview of DocILE 2023: Document Information Localization and Extraction Type Conference Article
  Year 2023 Publication International Conference of the Cross-Language Evaluation Forum for European Languages Abbreviated Journal  
  Volume 14163 Issue Pages 276–293  
  Keywords Information Extraction; Computer Vision; Natural Language Processing; Optical Character Recognition; Document Understanding  
  Abstract This paper provides an overview of the DocILE 2023 Competition, its tasks, participant submissions, the competition results and possible future research directions. This first edition of the competition focused on two Information Extraction tasks, Key Information Localization and Extraction (KILE) and Line Item Recognition (LIR). Both of these tasks require detection of pre-defined categories of information in business documents. The second task additionally requires correctly grouping the information into tuples, capturing the structure laid out in the document. The competition used the recently published DocILE dataset and benchmark that stays open to new submissions. The diversity of the participant solutions indicates the potential of the dataset as the submissions included pure Computer Vision, pure Natural Language Processing, as well as multi-modal solutions and utilized all of the parts of the dataset, including the annotated, synthetic and unlabeled subsets.  
  Address Thessaloniki; Greece; September 2023  
  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 CLEF  
  Notes DAG Approved no  
  Call Number Admin @ si @ SUS2023a Serial 3924  
Permanent link to this record
 

 
Author Gabriela Ramirez; Esau Villatoro; Bogdan Ionescu; Hugo Jair Escalante; Sergio Escalera; Martha Larson; Henning Muller; Isabelle Guyon edit  openurl
  Title (up) Overview of the Multimedia Information Processing for Personality & Social Networks Analysis Contes Type Conference Article
  Year 2018 Publication Multimedia Information Processing for Personality and Social Networks Analysis (MIPPSNA 2018) Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Beijing; China; August 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 ICPRW  
  Notes HUPBA Approved no  
  Call Number Admin @ si @ RVI2018 Serial 3211  
Permanent link to this record
 

 
Author Joan Serrat; X. Varona; Antonio Lopez; Xavier Roca; Juan J. Villanueva edit   pdf
openurl 
  Title (up) P3: a three-dimensional digitizer prototype. Type Miscellaneous
  Year 2001 Publication Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 1:315–322. Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Castellon.  
  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;ISE Approved no  
  Call Number ADAS @ adas @ SVL2001 Serial 213  
Permanent link to this record
 

 
Author Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Bemedi edit   pdf
doi  isbn
openurl 
  Title (up) Page Segmentation of Structured Documents Using 2D Stochastic Context-Free Grammars Type Conference Article
  Year 2013 Publication 6th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 7887 Issue Pages 133-140  
  Keywords  
  Abstract In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for page segmentation of structured documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the page segmentation is obtained as the most likely hypothesis according to a grammar. This approach is compared to Conditional Random Fields and results show significant improvements in several cases. Furthermore, grammars provide a detailed segmentation that allowed a semantic evaluation which also validates this model.  
  Address Madeira; Portugal; June 2013  
  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 978-3-642-38627-5 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG; 605.203 Approved no  
  Call Number Admin @ si @ ACS2013 Serial 2328  
Permanent link to this record
 

 
Author Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg edit  doi
openurl 
  Title (up) Painting-91: A Large Scale Database for Computational Painting Categorization Type Journal Article
  Year 2014 Publication Machine Vision and Applications Abbreviated Journal MVAP  
  Volume 25 Issue 6 Pages 1385-1397  
  Keywords  
  Abstract Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0932-8092 ISBN Medium  
  Area Expedition Conference  
  Notes CIC; LAMP; 600.074; 600.079 Approved no  
  Call Number Admin @ si @ KBW2014 Serial 2510  
Permanent link to this record
 

 
Author Robert Benavente; Maria Vanrell; Ramon Baldrich edit  openurl
  Title (up) Parametric Fuzzy Sets for Automatic Color Naming Type Journal
  Year 2008 Publication Journal of the Optical Society of America A Abbreviated Journal  
  Volume 25 Issue 10 Pages 2582–2593  
  Keywords  
  Abstract  
  Address  
  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 CIC Approved no  
  Call Number CAT @ cat @ BVB2008 Serial 1004  
Permanent link to this record
 

 
Author Robert Benavente; Maria Vanrell edit  openurl
  Title (up) Parametrizacion del Espacio de Categorias de Color Type Miscellaneous
  Year 2007 Publication Proceedings del VIII Congreso Nacional del Color Abbreviated Journal  
  Volume Issue Pages 77–78  
  Keywords  
  Abstract  
  Address Madrid (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 CNC’07  
  Notes CAT;CIC Approved no  
  Call Number CAT @ cat @ BeV2007 Serial 905  
Permanent link to this record
 

 
Author A. Quingles edit  openurl
  Title (up) Particio de sòlids Type Report
  Year 2001 Publication CVC Technical Report #54 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address CVC (UAB)  
  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 Approved no  
  Call Number Admin @ si @ Qui2001 Serial 206  
Permanent link to this record
 

 
Author Mariella Dimiccoli; Jean-Pascal Jacob; Lionel Moisan edit   pdf
url  openurl
  Title (up) Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach Type Journal Article
  Year 2016 Publication Journal of Machine Vision and Applications Abbreviated Journal MVAP  
  Volume 27 Issue Pages 511-527  
  Keywords particle detection; particle tracking; a-contrario approach; time-lapse fluorescence imaging  
  Abstract In this work, we propose a probabilistic approach for the detection and the
tracking of particles on biological images. In presence of very noised and poor
quality data, particles and trajectories can be characterized by an a-contrario
model, that estimates the probability of observing the structures of interest
in random data. This approach, first introduced in the modeling of human visual
perception and then successfully applied in many image processing tasks, leads
to algorithms that do not require a previous learning stage, nor a tedious
parameter tuning and are very robust to noise. Comparative evaluations against
a well established baseline show that the proposed approach outperforms the
state of the art.
 
  Address  
  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; Approved no  
  Call Number Admin @ si @ DJM2016 Serial 2735  
Permanent link to this record
 

 
Author Fernando Vilariño; Petia Radeva edit  url
openurl 
  Title (up) Patch-Optimized Discriminant Active Contours for Medical Image Segmentation. Type Conference Article
  Year 2002 Publication Iberoamerican Conference on Artificial Intelligence Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Sevilla, Espanya  
  Corporate Author Thesis  
  Publisher Springer Verlag 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 IBERAMIA  
  Notes MV;MILAB;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ ViR2002; IAM @ iam @ VRa2003 Serial 320  
Permanent link to this record
 

 
Author Debora Gil; Jaume Garcia; Mariano Vazquez; Ruth Aris; Guilleaume Houzeaux edit   pdf
isbn  openurl
  Title (up) Patient-Sensitive Anatomic and Functional 3D Model of the Left Ventricle Function Type Conference Article
  Year 2008 Publication 8th World Congress on Computational Mechanichs (WCCM8) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Left Ventricle, Electromechanical Models, Image Processing, Magnetic Resonance.  
  Abstract Early diagnosis and accurate treatment of Left Ventricle (LV) dysfunction significantly increases the patient survival. Impairment of LV contractility due to cardiovascular diseases is reflected in its motion patterns. Recent advances in medical imaging, such as Magnetic Resonance (MR), have encouraged research on 3D simulation and modelling of the LV dynamics. Most of the existing 3D models [1] consider just the gross anatomy of the LV and restore a truncated ellipse which deforms along the cardiac cycle. The contraction mechanics of any muscle strongly depends on the spatial orientation of its muscular fibers since the motion that the muscle undergoes mainly takes place along the fibers. It follows that such simplified models do not allow evaluation of the heart electro-mechanical function and coupling, which has recently risen as the key point for understanding the LV functionality [2]. In order to thoroughly understand the LV mechanics it is necessary to consider the complete anatomy of the LV given by the orientation of the myocardial fibres in 3D space as described by Torrent Guasp [3].
We propose developing a 3D patient-sensitive model of the LV integrating, for the first time, the ven- tricular band anatomy (fibers orientation), the LV gross anatomy and its functionality. Such model will represent the LV function as a natural consequence of its own ventricular band anatomy. This might be decisive in restoring a proper LV contraction in patients undergoing pace marker treatment.
The LV function is defined as soon as the propagation of the contractile electromechanical pulse has been modelled. In our experiments we have used the wave equation for the propagation of the electric pulse. The electromechanical wave moves on the myocardial surface and should have a conductivity tensor oriented along the muscular fibers. Thus, whatever mathematical model for electric pulse propa- gation [4] we consider, the complete anatomy of the LV should be extracted.
The LV gross anatomy is obtained by processing multi slice MR images recorded for each patient. Information about the myocardial fibers distribution can only be extracted by Diffusion Tensor Imag- ing (DTI), which can not provide in vivo information for each patient. As a first approach, we have
Figure 1: Scheme for the Left Ventricle Patient-Sensitive Model.
computed an average model of fibers from several DTI studies of canine hearts. This rough anatomy is the input for our electro-mechanical propagation model simulating LV dynamics. The average fiber orientation is updated until the simulated LV motion agrees with the experimental evidence provided by the LV motion observed in tagged MR (TMR) sequences. Experimental LV motion is recovered by applying image processing, differential geometry and interpolation techniques to 2D TMR slices [5]. The pipeline in figure 1 outlines the interaction between simulations and experimental data leading to our patient-tailored model.
 
  Address Venice; Italy  
  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 9788496736559 Medium  
  Area Expedition Conference  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ GGV2008b Serial 993  
Permanent link to this record
 

 
Author Debora Gil; Jaume Garcia; Manuel Vazquez; Ruth Aris; Guillaume Houzeaux edit   pdf
url  openurl
  Title (up) Patient-Sensitive Anatomic and Functional 3D Model of the Left Ventricle Function Type Conference Article
  Year 2008 Publication 8th World Congress on Computational Mechanichs (WCCM8)/5th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Left Ventricle; Electromechanical Models; Image Processing; Magnetic Resonance.  
  Abstract Early diagnosis and accurate treatment of Left Ventricle (LV) dysfunction significantly increases the patient survival. Impairment of LV contractility due to cardiovascular diseases is reflected in its motion patterns. Recent advances in medical imaging, such as Magnetic Resonance (MR), have encouraged research on 3D simulation and modelling of the LV dynamics. Most of the existing 3D models consider just the gross anatomy of the LV and restore a truncated ellipse which deforms along the cardiac cycle. The contraction mechanics of any muscle strongly depends on the spatial orientation of its muscular fibers since the motion that the muscle undergoes mainly takes place along the fibers. It follows that such simplified models do not allow evaluation of the heart electro-mechanical function and coupling, which has recently risen as the key point for understanding the LV functionality . In order to thoroughly understand the LV mechanics it is necessary to consider the complete anatomy of the LV given by the orientation of the myocardial fibres in 3D space as described by Torrent Guasp. We propose developing a 3D patient-sensitive model of the LV integrating, for the first time, the ven- tricular band anatomy (fibers orientation), the LV gross anatomy and its functionality. Such model will represent the LV function as a natural consequence of its own ventricular band anatomy. This might be decisive in restoring a proper LV contraction in patients undergoing pace marker treatment. The LV function is defined as soon as the propagation of the contractile electromechanical pulse has been modelled. In our experiments we have used the wave equation for the propagation of the electric pulse. The electromechanical wave moves on the myocardial surface and should have a conductivity tensor oriented along the muscular fibers. Thus, whatever mathematical model for electric pulse propa- gation [4] we consider, the complete anatomy of the LV should be extracted. The LV gross anatomy is obtained by processing multi slice MR images recorded for each patient. Information about the myocardial fibers distribution can only be extracted by Diffusion Tensor Imag- ing (DTI), which can not provide in vivo information for each patient. As a first approach, we have computed an average model of fibers from several DTI studies of canine hearts. This rough anatomy is the input for our electro-mechanical propagation model simulating LV dynamics. The average fiber orientation is updated until the simulated LV motion agrees with the experimental evidence provided by the LV motion observed in tagged MR (TMR) sequences. Experimental LV motion is recovered by applying image processing, differential geometry and interpolation techniques to 2D TMR slices [5]. The pipeline in figure 1 outlines the interaction between simulations and experimental data leading to our patient-tailored model.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Venezia (Italia) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN B-31470-08 ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGV2008c Serial 1521  
Permanent link to this record
 

 
Author Jaume Garcia; Debora Gil; Francesc Carreras; Sandra Pujades; R.Leta; Xavier Alomar; Guillem Pons-LLados edit   pdf
url  openurl
  Title (up) Patrons de Normalitat Regional per la Valoració de la Funció del Ventricle Esquerre Type Conference Article
  Year 2008 Publication XX Congrés de la Societat Catalana de Cardiologia Abbreviated Journal  
  Volume Issue Pages 60  
  Keywords  
  Abstract Les malalties cardiovasculars afecten les propietats contràctils de la banda ventricular i provoquen una variació de la funció del Ventricle Esquerre (VE) . Només els indicadors locals (strains, la deformació del teixit) són capaços de detectar anomalies en territoris específics del VE . Patrons de normalitat regionals d’aquests paràmetres serien d’utilitat a l’hora de valorar-ne la funció .
Presentem un Domini Paramètric Normalitzat (DPN) que permet comparar dades de diferents pacients i definir Patrons de Normalitat Regional (PNR)
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Barcelona Editor  
  Language catalan Summary Language catalan 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 @ GGC2008b Serial 1503  
Permanent link to this record
 

 
Author Joan Marti; Jose Miguel Benedi; Ana Maria Mendonça; Joan Serrat edit  openurl
  Title (up) Pattern Recognition and Image Analysis Type Book Whole
  Year 2007 Publication 3rd Iberian Conference Abbreviated Journal  
  Volume 6669 Issue Pages 4477-4478  
  Keywords  
  Abstract  
  Address Girona (Spain)  
  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 IbPRIA  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ MBM2007 Serial 994  
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