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Author Jose Seabra; F. Javier Sanchez; Francesco Ciompi; Petia Radeva edit  url
doi  isbn
openurl 
  Title Ultrasonographic Plaque Characterization using a Rayleigh Mixture Model Type Conference Article
  Year 2010 Publication 7th IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
  Volume Issue Pages 1–4  
  Keywords  
  Abstract From Nano to Macro
A correct modelling of tissue morphology is determinant for the identification of vulnerable plaques. This paper aims at describing the plaque composition by means of a Rayleigh Mixture Model applied to ultrasonic data. The effectiveness of using a mixture of distributions is established through synthetic and real ultrasonic data samples. Furthermore, the proposed mixture model is used in a plaque classification problem in Intravascular Ultrasound (IVUS) images of coronary plaques. A classifier tested on a set of 67 in-vitro plaques, yields an overall accuracy of 86% and sensitivity of 92%, 94% and 82%, for fibrotic, calcified and lipidic tissues, respectively. These results strongly suggest that different plaques types can be distinguished by means of the coefficients and Rayleigh parameters of the mixture distribution.
 
  Address (up) Rotterdam (Netherlands)  
  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 1945-7928 ISBN 978-1-4244-4125-9 Medium  
  Area Expedition Conference ISBI  
  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SSC2010 Serial 1366  
Permanent link to this record
 

 
Author Carles Sanchez; Debora Gil; T. Gache; N. Koufos; Marta Diez-Ferrer; Antoni Rosell edit   pdf
openurl 
  Title SENSA: a System for Endoscopic Stenosis Assessment Type Conference Article
  Year 2016 Publication 28th Conference of the international Society for Medical Innovation and Technology Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Documenting the severity of a static or dynamic Central Airway Obstruction (CAO) is crucial to establish proper diagnosis and treatment, predict possible treatment effects and better follow-up the patients. The subjective visual evaluation of a stenosis during video-bronchoscopy still remains the most common way to assess a CAO in spite of a consensus among experts for a need to standardize all calculations [1].
The Computer Vision Center in cooperation with the «Hospital de Bellvitge», has developed a System for Endoscopic Stenosis Assessment (SENSA), which computes CAO directly by analyzing standard bronchoscopic data without the need of using other imaging tecnologies.
 
  Address (up) Rotterdam; The Netherlands; October 2016  
  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 SMIT  
  Notes IAM; Approved no  
  Call Number Admin @ si @ SGG2016 Serial 2942  
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Author Ernest Valveny; Miquel Ferrer edit  openurl
  Title Application of Graph Embedding to Solve Graph Matchin Problems Type Conference Article
  Year 2008 Publication Colloque International Francophone sur l’Ecrit et le Document Abbreviated Journal  
  Volume Issue Pages 13–18  
  Keywords  
  Abstract  
  Address (up) Rouen (France)  
  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 CIFED’08  
  Notes DAG Approved no  
  Call Number DAG @ dag @ VaF2008 Serial 1063  
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Author H. Chouaib; Salvatore Tabbone; Oriol Ramos Terrades; F. Cloppet; N. Vincent; A.T. Thierry Paquet edit  openurl
  Title Sélection de Caractéristiques à partir d'un algorithme génétique et d'une combinaison de classifieurs Adaboost Type Conference Article
  Year 2008 Publication Colloque International Francophone sur l'Ecrit et le Document Abbreviated Journal  
  Volume Issue Pages 181-186  
  Keywords  
  Abstract  
  Address (up) Rouen, France  
  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 CIFED  
  Notes DAG Approved no  
  Call Number Admin @ si @ CTR2008 Serial 1874  
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Author T.O. Nguyen; Salvatore Tabbone; Oriol Ramos Terrades; A.T. Thierry edit  openurl
  Title Proposition d'un descripteur de formes et du modèle vectoriel pour la recherche de symboles Type Conference Article
  Year 2008 Publication Colloque International Francophone sur l'Ecrit et le Document Abbreviated Journal  
  Volume Issue Pages 79-84  
  Keywords  
  Abstract  
  Address (up) Rouen, France  
  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 CIFED  
  Notes DAG Approved no  
  Call Number Admin @ si @ NTR2008b Serial 1875  
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Author Clement Guerin; Christophe Rigaud; Karell Bertet; Jean-Christophe Burie; Arnaud Revel ; Jean-Marc Ogier edit  openurl
  Title Réduction de l’espace de recherche pour les personnages de bandes dessinées Type Conference Article
  Year 2014 Publication 19th National Congress Reconnaissance de Formes et l'Intelligence Artificielle Abbreviated Journal  
  Volume Issue Pages  
  Keywords contextual search; document analysis; comics characters  
  Abstract Les bandes dessinées représentent un patrimoine culturel important dans de nombreux pays et leur numérisation massive offre la possibilité d'effectuer des recherches dans le contenu des images. À ce jour, ce sont principalement les structures des pages et leurs contenus textuels qui ont été étudiés, peu de travaux portent sur le contenu graphique. Nous proposons de nous appuyer sur des éléments déjà étudiés tels que la position des cases et des bulles, pour réduire l'espace de recherche et localiser les personnages en fonction de la queue des bulles. L'évaluation de nos différentes contributions à partir de la base eBDtheque montre un taux de détection des queues de bulle de 81.2%, de localisation des personnages allant jusqu'à 85% et un gain d'espace de recherche de plus de 50%.  
  Address (up) Rouen; Francia; July 2014  
  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 RFIA  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ GRB2014 Serial 2480  
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Author Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero edit  doi
openurl 
  Title Banknote counterfeit detection through background texture printing analysis Type Conference Article
  Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This paper is focused on the detection of counterfeit photocopy banknotes. The main difficulty is to work on a real industrial scenario without any constraint about the acquisition device and with a single image. The main contributions of this paper are twofold: first the adaptation and performance evaluation of existing approaches to classify the genuine and photocopy banknotes using background texture printing analysis, which have not been applied into this context before. Second, a new dataset of Euro banknotes images acquired with several cameras under different luminance conditions to evaluate these methods. Experiments on the proposed algorithms show that mixing SIFT features and sparse coding dictionaries achieves quasi perfect classification using a linear SVM with the created dataset. Approaches using dictionaries to cover all possible texture variations have demonstrated to be robust and outperform the state-of-the-art methods using the proposed benchmark.  
  Address (up) Rumania; May 2016  
  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 DAS  
  Notes DAG; 600.061; 601.269; 600.097 Approved no  
  Call Number Admin @ si @ BRL2016 Serial 2950  
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Author Joost Van de Weijer; Fahad Shahbaz Khan edit   pdf
openurl 
  Title An Overview of Color Name Applications in Computer Vision Type Conference Article
  Year 2015 Publication Computational Color Imaging Workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords color features; color names; object recognition  
  Abstract 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.  
  Address (up) Saint Etienne; France; March 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 CCIW  
  Notes LAMP; 600.079; 600.068 Approved no  
  Call Number Admin @ si @ WeK2015 Serial 2586  
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Author Xavier Otazu; Maria Vanrell edit  openurl
  Title Several lightness induction effects with a computational multiresolution wavelet framework Type Journal
  Year 2006 Publication 29th European Conference on Visual Perception (ECVP’06), Perception Suppl s, 32: 56–56 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Saint-Petersburg (Russia)  
  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 @ OtV2006 Serial 659  
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Author V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich edit  openurl
  Title Pattern Recognition of Fragmented Objects with Adaptive Correlation Filters Type Miscellaneous
  Year 2006 Publication Topical Meeting on Optoinformatics / Information Photonics, 150–151 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Saint-Petersburg (Russia)  
  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 ISE Approved no  
  Call Number ISE @ ise @ KMA2006b Serial 674  
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Author Mikhail Mozerov; V. Kober; I.A. Ovseyevich edit  openurl
  Title A Stereo Matching Algorithm with Global Smoothness Criterion Type Miscellaneous
  Year 2006 Publication Topical Meeting on Optoinformatics / Information Photonics, 133–135 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Saint-Petersburg (Russia)  
  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 ISE Approved no  
  Call Number ISE @ ise @ MKO2006 Serial 675  
Permanent link to this record
 

 
Author Eduardo Aguilar; Petia Radeva edit  url
openurl 
  Title Class-Conditional Data Augmentation Applied to Image Classification Type Conference Article
  Year 2019 Publication 18th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 11679 Issue Pages 182-192  
  Keywords CNNs; Data augmentation; Deep learning; Epistemic uncertainty; Image classification; Food recognition  
  Abstract Image classification is widely researched in the literature, where models based on Convolutional Neural Networks (CNNs) have provided better results. When data is not enough, CNN models tend to be overfitted. To deal with this, often, traditional techniques of data augmentation are applied, such as: affine transformations, adjusting the color balance, among others. However, we argue that some techniques of data augmentation may be more appropriate for some of the classes. In order to select the techniques that work best for particular class, we propose to explore the epistemic uncertainty for the samples within each class. From our experiments, we can observe that when the data augmentation is applied class-conditionally, we improve the results in terms of accuracy and also reduce the overall epistemic uncertainty. To summarize, in this paper we propose a class-conditional data augmentation procedure that allows us to obtain better results and improve robustness of the classification in the face of model uncertainty.  
  Address (up) Salermo; Italy; September 2019  
  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 CAIP  
  Notes MILAB; no proj Approved no  
  Call Number Admin @ si @ AgR2019 Serial 3366  
Permanent link to this record
 

 
Author Estefania Talavera; Nicolai Petkov; Petia Radeva edit   pdf
url  doi
openurl 
  Title Unsupervised Routine Discovery in Egocentric Photo-Streams Type Conference Article
  Year 2019 Publication 18th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 11678 Issue Pages 576-588  
  Keywords Routine discovery; Lifestyle; Egocentric vision; Behaviour analysis  
  Abstract The routine of a person is defined by the occurrence of activities throughout different days, and can directly affect the person’s health. In this work, we address the recognition of routine related days. To do so, we rely on egocentric images, which are recorded by a wearable camera and allow to monitor the life of the user from a first-person view perspective. We propose an unsupervised model that identifies routine related days, following an outlier detection approach. We test the proposed framework over a total of 72 days in the form of photo-streams covering around 2 weeks of the life of 5 different camera wearers. Our model achieves an average of 76% Accuracy and 68% Weighted F-Score for all the users. Thus, we show that our framework is able to recognise routine related days and opens the door to the understanding of the behaviour of people.  
  Address (up) Salermo; Italy; September 2019  
  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 CAIP  
  Notes MILAB; no proj Approved no  
  Call Number Admin @ si @ TPR2019a Serial 3367  
Permanent link to this record
 

 
Author Joan Arnedo-Moreno; D. Bañeres; Xavier Baro; S. Caballe; S. Guerrero; L. Porta; J. Prieto edit  doi
isbn  openurl
  Title Va-ID: A trust-based virtual assessment system Type Conference Article
  Year 2014 Publication 6th International Conference on Intelligent Networking and Collaborative Systems Abbreviated Journal  
  Volume Issue Pages 328 - 335  
  Keywords  
  Abstract Even though online education is a very important pillar of lifelong education, institutions are still reluctant to wager for a fully online educational model. At the end, they keep relying on on-site assessment systems, mainly because fully virtual alternatives do not have the deserved social recognition or credibility. Thus, the design of virtual assessment systems that are able to provide effective proof of student authenticity and authorship and the integrity of the activities in a scalable and cost efficient manner would be very helpful. This paper presents ValID, a virtual assessment approach based on a continuous trust level evaluation between students and the institution. The current trust level serves as the main mechanism to dynamically decide which kind of controls a given student should be subjected to, across different courses in a degree. The main goal is providing a fair trade-off between security, scalability and cost, while maintaining the perceived quality of the educational model.  
  Address (up) Salerna; Italy; September 2014  
  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 978-1-4799-6386-7 Medium  
  Area Expedition Conference INCOS  
  Notes OR; HuPBA;MV Approved no  
  Call Number Admin @ si @ ABB2014 Serial 2620  
Permanent link to this record
 

 
Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Petia Radeva edit  doi
isbn  openurl
  Title Multi-class Binary Symbol Classification with Circular Blurred Shape Models Type Conference Article
  Year 2009 Publication 15th International Conference on Image Analysis and Processing Abbreviated Journal  
  Volume 5716 Issue Pages 1005–1014  
  Keywords  
  Abstract Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements.  
  Address (up) Salerno, Italy  
  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 978-3-642-04145-7 Medium  
  Area Expedition Conference ICIAP  
  Notes MILAB;HuPBA;DAG Approved no  
  Call Number BCNPCL @ bcnpcl @ EFP2009c Serial 1186  
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