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Author Andrei Polzounov; Artsiom Ablavatski; Sergio Escalera; Shijian Lu; Jianfei Cai edit  doi
openurl 
  Title (down) WordFences: Text Localization and Recognition Type Conference Article
  Year 2017 Publication 24th International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Beijing; China; September 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 ICIP  
  Notes HUPBA; no menciona Approved no  
  Call Number Admin @ si @ PAE2017 Serial 3007  
Permanent link to this record
 

 
Author Xim Cerda-Company; C. Alejandro Parraga; Xavier Otazu edit  openurl
  Title (down) Which tone-mapping is the best? A comparative study of tone-mapping perceived quality Type Abstract
  Year 2014 Publication Perception Abbreviated Journal  
  Volume 43 Issue Pages 106  
  Keywords  
  Abstract Perception 43 ECVP Abstract Supplement
High-dynamic-range (HDR) imaging refers to the methods designed to increase the brightness dynamic range present in standard digital imaging techniques. This increase is achieved by taking the same picture under di erent exposure values and mapping the intensity levels into a single image by way of a tone-mapping operator (TMO). Currently, there is no agreement on how to evaluate the quality
of di erent TMOs. In this work we psychophysically evaluate 15 di erent TMOs obtaining rankings based on the perceived properties of the resulting tone-mapped images. We performed two di erent experiments on a CRT calibrated display using 10 subjects: (1) a study of the internal relationships between grey-levels and (2) a pairwise comparison of the resulting 15 tone-mapped images. In (1) observers internally matched the grey-levels to a reference inside the tone-mapped images and in the real scene. In (2) observers performed a pairwise comparison of the tone-mapped images alongside the real scene. We obtained two rankings of the TMOs according their performance. In (1) the best algorithm
was ICAM by J.Kuang et al (2007) and in (2) the best algorithm was a TMO by Krawczyk et al (2005). Our results also show no correlation between these two rankings.
 
  Address  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECVP  
  Notes NEUROBIT; 600.074 Approved no  
  Call Number Admin @ si @ CPO2014 Serial 2527  
Permanent link to this record
 

 
Author Javad Zolfaghari Bengar; Bogdan Raducanu; Joost Van de Weijer edit  url
openurl 
  Title (down) When Deep Learners Change Their Mind: Learning Dynamics for Active Learning Type Conference Article
  Year 2021 Publication 19th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 13052 Issue 1 Pages 403-413  
  Keywords  
  Abstract Active learning aims to select samples to be annotated that yield the largest performance improvement for the learning algorithm. Many methods approach this problem by measuring the informativeness of samples and do this based on the certainty of the network predictions for samples. However, it is well-known that neural networks are overly confident about their prediction and are therefore an untrustworthy source to assess sample informativeness. In this paper, we propose a new informativeness-based active learning method. Our measure is derived from the learning dynamics of a neural network. More precisely we track the label assignment of the unlabeled data pool during the training of the algorithm. We capture the learning dynamics with a metric called label-dispersion, which is low when the network consistently assigns the same label to the sample during the training of the network and high when the assigned label changes frequently. We show that label-dispersion is a promising predictor of the uncertainty of the network, and show on two benchmark datasets that an active learning algorithm based on label-dispersion obtains excellent results.  
  Address September 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 CAIP  
  Notes LAMP; Approved no  
  Call Number Admin @ si @ ZRV2021 Serial 3673  
Permanent link to this record
 

 
Author Felipe Lumbreras; Joan Serrat edit  doi
openurl 
  Title (down) Wavelet filtering for the segmentation of marble images. Type Journal Article
  Year 1996 Publication Optical Engineering Abbreviated Journal  
  Volume 35 Issue 10 Pages  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  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 @ LuS1996a Serial 77  
Permanent link to this record
 

 
Author Yagmur Gucluturk; Umut Guclu; Marc Perez; Hugo Jair Escalante; Xavier Baro; Isabelle Guyon; Carlos Andujar; Julio C. S. Jacques Junior; Meysam Madadi; Sergio Escalera edit   pdf
doi  openurl
  Title (down) Visualizing Apparent Personality Analysis with Deep Residual Networks Type Conference Article
  Year 2017 Publication Chalearn Workshop on Action, Gesture, and Emotion Recognition: Large Scale Multimodal Gesture Recognition and Real versus Fake expressed emotions at ICCV Abbreviated Journal  
  Volume Issue Pages 3101-3109  
  Keywords  
  Abstract Automatic prediction of personality traits is a subjective task that has recently received much attention. Specifically, automatic apparent personality trait prediction from multimodal data has emerged as a hot topic within the filed of computer vision and, more particularly, the so called “looking
at people” sub-field. Considering “apparent” personality traits as opposed to real ones considerably reduces the subjectivity of the task. The real world applications are encountered in a wide range of domains, including entertainment, health, human computer interaction, recruitment and security. Predictive models of personality traits are useful for individuals in many scenarios (e.g., preparing for job interviews, preparing for public speaking). However, these predictions in and of themselves might be deemed to be untrustworthy without human understandable supportive evidence. Through a series of experiments on a recently released benchmark dataset for automatic apparent personality trait prediction, this paper characterizes the audio and
visual information that is used by a state-of-the-art model while making its predictions, so as to provide such supportive evidence by explaining predictions made. Additionally, the paper describes a new web application, which gives feedback on apparent personality traits of its users by combining
model predictions with their explanations.
 
  Address Venice; Italy; October 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 ICCVW  
  Notes HUPBA; 6002.143 Approved no  
  Call Number Admin @ si @ GGP2017 Serial 3067  
Permanent link to this record
 

 
Author A. Martinez; Jordi Vitria; J. Lopez edit  openurl
  Title (down) Visual Recognition of Surroundings: A robot that knows where it is. Type Conference Article
  Year 1997 Publication Actes de la conférence Artificielle et Complexite. Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Paris.  
  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;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ MVL1997 Serial 59  
Permanent link to this record
 

 
Author J. Pladellorens; Joan Serrat; A. Castell; M.J. Yzuel edit  doi
openurl 
  Title (down) Using mathematical morphology to determine left ventricular contours. Type Journal
  Year 1993 Publication Physics in Medicine and Biology. Abbreviated Journal  
  Volume 38 Issue 12 Pages 1877––1894  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ PSC1993 Serial 146  
Permanent link to this record
 

 
Author Josep Llados; Horst Bunke; Enric Marti edit  doi
openurl 
  Title (down) Using cyclic string matching to find rotational and reflectional symmetric shapes Type Conference Article
  Year 1996 Publication Intelligent Robots: Sensing, Modeling and Planning (Dagstuhl Workshop) Abbreviated Journal  
  Volume Issue Pages 164-179  
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  Abstract  
  Address  
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  Publisher World Scientific Place of Publication Saarbrucken (Germany). Editor R.C. Bolles, H.B.H.N.  
  Language Summary Language Original Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM Approved no  
  Call Number IAM @ iam @ LBM1996 Serial 1564  
Permanent link to this record
 

 
Author Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris edit  url
openurl 
  Title (down) Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code Type Conference Article
  Year 2015 Publication European Conference on Visual Perception ECVP2015 Abbreviated Journal  
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  Address Liverpool; uk; August 2015  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECVP  
  Notes NEUROBIT; Approved no  
  Call Number Admin @ si @ POW2015 Serial 2633  
Permanent link to this record
 

 
Author David Lloret; Joan Serrat; Antonio Lopez; Juan J. Villanueva edit   pdf
doi  openurl
  Title (down) Ultrasound to MR Volume Registration for Brain Sinking Measurement Type Conference Article
  Year 2003 Publication 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 Abbreviated Journal  
  Volume 2652 Issue Pages 420-427  
  Keywords  
  Abstract  
  Address Springer-Verlag  
  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 @ LSL2003a Serial 384  
Permanent link to this record
 

 
Author A. Auge; Javier Varona; Juan J. Villanueva edit  openurl
  Title (down) Tumour Segmentation in Mammographies with Neural Networks. Application to Tumoural Volume Approximation. Type Conference Article
  Year 1997 Publication (SNRFAI’97) 7th Spanish National Symposium on Pattern Recognition and Image Analysis. Abbreviated Journal  
  Volume Issue Pages  
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  Notes Approved no  
  Call Number ISE @ ise @ AVV1997 Serial 208  
Permanent link to this record
 

 
Author B. Gotschy; Matthias S. Keil; H. Klos; I. Rystau edit  doi
openurl 
  Title (down) Transition from static to dynamic Jahn-Teller distortion in (P(C6 H5)4)2 C60| Type Journal Article
  Year 1994 Publication Solid State Communications Abbreviated Journal  
  Volume 92 Issue 12 Pages 935-938  
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  Notes Approved no  
  Call Number Admin @ si @ GKK1994 Serial 631  
Permanent link to this record
 

 
Author Hector Laria Mantecon; Yaxing Wang; Joost Van de Weijer; Bogdan Raducanu edit  doi
openurl 
  Title (down) Transferring Unconditional to Conditional GANs With Hyper-Modulation Type Conference Article
  Year 2022 Publication IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract GANs have matured in recent years and are able to generate high-resolution, realistic images. However, the computational resources and the data required for the training of high-quality GANs are enormous, and the study of transfer learning of these models is therefore an urgent topic. Many of the available high-quality pretrained GANs are unconditional (like StyleGAN). For many applications, however, conditional GANs are preferable, because they provide more control over the generation process, despite often suffering more training difficulties. Therefore, in this paper, we focus on transferring from high-quality pretrained unconditional GANs to conditional GANs. This requires architectural adaptation of the pretrained GAN to perform the conditioning. To this end, we propose hyper-modulated generative networks that allow for shared and complementary supervision. To prevent the additional weights of the hypernetwork to overfit, with subsequent mode collapse on small target domains, we introduce a self-initialization procedure that does not require any real data to initialize the hypernetwork parameters. To further improve the sample efficiency of the transfer, we apply contrastive learning in the discriminator, which effectively works on very limited batch sizes. In extensive experiments, we validate the efficiency of the hypernetworks, self-initialization and contrastive loss for knowledge transfer on standard benchmarks.  
  Address New Orleans; USA; June 2022  
  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 CVPRW  
  Notes LAMP; 600.147; 602.200 Approved no  
  Call Number LWW2022a Serial 3785  
Permanent link to this record
 

 
Author Antonio Lopez; Joan Serrat edit  doi
openurl 
  Title (down) Tracing crease curves by solving a system of differential equations. Type Conference Article
  Year 1996 Publication ECCV 1996 Abbreviated Journal  
  Volume 1064 Issue Pages  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ LoS1996 Serial 84  
Permanent link to this record
 

 
Author Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Gloria Fernandez Esparrach; Xavier Gray; Olivier Romain; F. Javier Sanchez; Aymeric Histace edit   pdf
doi  openurl
  Title (down) Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis Type Conference Article
  Year 2017 Publication 4th International Workshop on Computer Assisted and Robotic Endoscopy Abbreviated Journal  
  Volume Issue Pages 29-41  
  Keywords Polyp detection; colonoscopy; real time; spatio temporal coherence  
  Abstract Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been proposed but none of them are used in the clinical room mainly due to computational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability module and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detection method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our
adaptation strategy.
 
  Address Quebec; Canada; September 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 CARE  
  Notes MV; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ ABS2017b Serial 2977  
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