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Author Albert Tatjer; Bhalaji Nagarajan; Ricardo Marques; Petia Radeva edit  url
openurl 
  Title CCLM: Class-Conditional Label Noise Modelling Type Conference Article
  Year 2023 Publication 11th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 14062 Issue Pages 3-14  
  Keywords  
  Abstract The performance of deep neural networks highly depends on the quality and volume of the training data. However, cost-effective labelling processes such as crowdsourcing and web crawling often lead to data with noisy (i.e., wrong) labels. Making models robust to this label noise is thus of prime importance. A common approach is using loss distributions to model the label noise. However, the robustness of these methods highly depends on the accuracy of the division of training set into clean and noisy samples. In this work, we dive in this research direction highlighting the existing problem of treating this distribution globally and propose a class-conditional approach to split the clean and noisy samples. We apply our approach to the popular DivideMix algorithm and show how the local treatment fares better with respect to the global treatment of loss distribution. We validate our hypothesis on two popular benchmark datasets and show substantial improvements over the baseline experiments. We further analyze the effectiveness of the proposal using two different metrics – Noise Division Accuracy and Classiness.  
  Address Alicante; Spain; June 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 IbPRIA  
  Notes MILAB Approved no  
  Call Number (up) Admin @ si @ TNM2023 Serial 3925  
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Author Guillermo Torres; Debora Gil edit  openurl
  Title A multi-shape loss function with adaptive class balancing for the segmentation of lung structures Type Journal Article
  Year 2020 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCAR  
  Volume 15 Issue 1 Pages S154-55  
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  Notes IAM Approved no  
  Call Number (up) Admin @ si @ ToG2020 Serial 3590  
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Author Ricardo Toledo edit  openurl
  Title Cardiac workstation and dynamic model to assist in coronary tree analysis. Type Book Whole
  Year 2001 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Place of Publication Editor Petia Radeva;JuanJose Villanueva  
  Language Summary Language Original Title  
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  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number (up) Admin @ si @ Tol2001 Serial 166  
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Author Juan Ignacio Toledo edit  isbn
openurl 
  Title Information Extraction from Heterogeneous Handwritten Documents Type Book Whole
  Year 2019 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In this thesis we explore information Extraction from totally or partially handwritten documents. Basically we are dealing with two different application scenarios. The first scenario are modern highly structured documents like forms. In this kind of documents, the semantic information is encoded in different fields with a pre-defined location in the document, therefore, information extraction becomes roughly equivalent to transcription. The second application scenario are loosely structured totally handwritten documents, besides transcribing them, we need to assign a semantic label, from a set of known values to the handwritten words.
In both scenarios, transcription is an important part of the information extraction. For that reason in this thesis we present two methods based on Neural Networks, to transcribe handwritten text.In order to tackle the challenge of loosely structured documents, we have produced a benchmark, consisting of a dataset, a defined set of tasks and a metric, that was presented to the community as an international competition. Also, we propose different models based on Convolutional and Recurrent neural networks that are able to transcribe and assign different semantic labels to each handwritten words, that is, able to perform Information Extraction.
 
  Address July 2019  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Alicia Fornes;Josep Llados  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-948531-7-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.140; 600.121 Approved no  
  Call Number (up) Admin @ si @ Tol2019 Serial 3389  
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Author Maria Ines Torres; Javier Mikel Olaso; Cesar Montenegro; Riberto Santana; A.Vazquez; Raquel Justo; J.A.Lozano; Stephan Schogl; Gerard Chollet; Nazim Dugan; M.Irvine; N.Glackin; C.Pickard; Anna Esposito; Gennaro Cordasco; Alda Troncone; Dijana Petrovska Delacretaz; Aymen Mtibaa; Mohamed Amine Hmani; M.S.Korsnes; L.J.Martinussen; Sergio Escalera; C.Palmero Cantariño; Olivier Deroo; O.Gordeeva; Jofre Tenorio Laranga; E.Gonzalez Fraile; Begoña Fernandez Ruanova; A.Gonzalez Pinto edit   pdf
url  openurl
  Title The EMPATHIC project: mid-term achievements Type Conference Article
  Year 2019 Publication 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments Abbreviated Journal  
  Volume Issue Pages 629-638  
  Keywords  
  Abstract Maria Ines Torres; Javier Mikel Olaso, César Montenegro, Riberto Santana, A. Vázquez, Raquel Justo, J. A. Lozano, Stephan Schlögl, Gérard Chollet, Nazim Dugan, M. Irvine, N. Glackin, C. Pickard, Anna Esposito, Gennaro Cordasco, Alda Troncone, Dijana Petrovska-Delacrétaz, Aymen Mtibaa, Mohamed Amine Hmani, M. S. Korsnes, L. J. Martinussen, Sergio Escalera, C. Palmero Cantariño, Olivier Deroo, O. Gordeeva, Jofre Tenorio-Laranga, E. Gonzalez-Fraile, Begoña Fernández-Ruanova, A. Gonzalez-Pinto  
  Address Rhodes Greece; June 2019  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference PETRA  
  Notes HUPBA; no proj Approved no  
  Call Number (up) Admin @ si @ TOM2019 Serial 3325  
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Author G. Tortajada edit  openurl
  Title Extraccio interactiva de patrocinadors d’anuncis en revistes utilitzant tecniques de Visio per Computador Type Report
  Year 2000 Publication CVC Technical Report #42 Abbreviated Journal  
  Volume Issue Pages  
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  Address CVC (UAB)  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) Admin @ si @ Tor2000b Serial 343  
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Author Francesc Tous edit  openurl
  Title Study of Colour Normalisation for Skin Detection. Type Miscellaneous
  Year 2002 Publication Director: M. Vanrell, Master Thesis. Abbreviated Journal  
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  Notes Approved no  
  Call Number (up) Admin @ si @ Tou2002 Serial 325  
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Author G.Thorvaldsen; Joana Maria Pujadas-Mora; T.Andersen ; L.Eikvil; Josep Llados; Alicia Fornes; Anna Cabre edit  url
openurl 
  Title A Tale of two Transcriptions Type Journal
  Year 2015 Publication Historical Life Course Studies Abbreviated Journal  
  Volume 2 Issue Pages 1-19  
  Keywords Nominative Sources; Census; Vital Records; Computer Vision; Optical Character Recognition; Word Spotting  
  Abstract non-indexed
This article explains how two projects implement semi-automated transcription routines: for census sheets in Norway and marriage protocols from Barcelona. The Spanish system was created to transcribe the marriage license books from 1451 to 1905 for the Barcelona area; one of the world’s longest series of preserved vital records. Thus, in the Project “Five Centuries of Marriages” (5CofM) at the Autonomous University of Barcelona’s Center for Demographic Studies, the Barcelona Historical Marriage Database has been built. More than 600,000 records were transcribed by 150 transcribers working online. The Norwegian material is cross-sectional as it is the 1891 census, recorded on one sheet per person. This format and the underlining of keywords for several variables made it more feasible to semi-automate data entry than when many persons are listed on the same page. While Optical Character Recognition (OCR) for printed text is scientifically mature, computer vision research is now focused on more difficult problems such as handwriting recognition. In the marriage project, document analysis methods have been proposed to automatically recognize the marriage licenses. Fully automatic recognition is still a challenge, but some promising results have been obtained. In Spain, Norway and elsewhere the source material is available as scanned pictures on the Internet, opening up the possibility for further international cooperation concerning automating the transcription of historic source materials. Like what is being done in projects to digitize printed materials, the optimal solution is likely to be a combination of manual transcription and machine-assisted recognition also for hand-written sources.
 
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  Series Volume Series Issue Edition  
  ISSN 2352-6343 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.077; 602.006 Approved no  
  Call Number (up) Admin @ si @ TPA2015 Serial 2582  
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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 Salermo; Italy; September 2019  
  Corporate Author Thesis  
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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 CAIP  
  Notes MILAB; no proj Approved no  
  Call Number (up) Admin @ si @ TPR2019a Serial 3367  
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Author Estefania Talavera; Nicolai Petkov; Petia Radeva edit  url
openurl 
  Title Towards Unsupervised Familiar Scene Recognition in Egocentric Videos Type Miscellaneous
  Year 2019 Publication Arxiv Abbreviated Journal  
  Volume Issue Pages  
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  Abstract CoRR abs/1905.04093
Nowadays, there is an upsurge of interest in using lifelogging devices. Such devices generate huge amounts of image data; consequently, the need for automatic methods for analyzing and summarizing these data is drastically increasing. We present a new method for familiar scene recognition in egocentric videos, based on background pattern detection through automatically configurable COSFIRE filters. We present some experiments over egocentric data acquired with the Narrative Clip.
 
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  Notes MILAB; no menciona Approved no  
  Call Number (up) Admin @ si @ TPR2019b Serial 3379  
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Author L.Tarazon; D. Perez; N. Serrano; V. Alabau; Oriol Ramos Terrades; A. Sanchis; A. Juan edit  doi
isbn  openurl
  Title Confidence Measures for Error Correction in Interactive Transcription of Handwritten Text Type Conference Article
  Year 2009 Publication 15th International Conference on Image Analysis and Processing Abbreviated Journal  
  Volume 5716 Issue Pages 567-574  
  Keywords  
  Abstract An effective approach to transcribe old text documents is to follow an interactive-predictive paradigm in which both, the system is guided by the human supervisor, and the supervisor is assisted by the system to complete the transcription task as efficiently as possible. In this paper, we focus on a particular system prototype called GIDOC, which can be seen as a first attempt to provide user-friendly, integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. More specifically, we focus on the handwriting recognition part of GIDOC, for which we propose the use of confidence measures to guide the human supervisor in locating possible system errors and deciding how to proceed. Empirical results are reported on two datasets showing that a word error rate not larger than a 10% can be achieved by only checking the 32% of words that are recognised with less confidence.  
  Address Vietri sul Mare, 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 DAG Approved no  
  Call Number (up) Admin @ si @ TPS2009 Serial 1871  
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Author Salvatore Tabbone; Oriol Ramos Terrades; S. Barrat edit  doi
openurl 
  Title Histogram of radon transform. A useful descriptor for shape retrieval Type Conference Article
  Year 2008 Publication 19th International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1-4  
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  Address Tampa, Florida  
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  Area Expedition Conference ICPR  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ TRB2008 Serial 1876  
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Author Guillermo Torres; Jan Rodríguez Dueñas; Sonia Baeza; Antoni Rosell; Carles Sanchez; Debora Gil edit   pdf
url  openurl
  Title Prediction of Malignancy in Lung Cancer using several strategies for the fusion of Multi-Channel Pyradiomics Images Type Conference Article
  Year 2023 Publication 7th Workshop on Digital Image Processing for Medical and Automotive Industry in the framework of SYNASC 2023 Abbreviated Journal  
  Volume Issue Pages  
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  Abstract This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level.  
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  ISSN ISBN Medium  
  Area Expedition Conference DIPMAI  
  Notes IAM Approved no  
  Call Number (up) Admin @ si @ TRB2023 Serial 3926  
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Author Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas edit   pdf
url  doi
openurl 
  Title Evaluating Real-Time Mirroring of Head Gestures using Smart Glasses Type Conference Article
  Year 2015 Publication 16th IEEE International Conference on Computer Vision Workshops Abbreviated Journal  
  Volume Issue Pages 452-460  
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  Abstract Mirroring occurs when one person tends to mimic the non-verbal communication of their counterparts. Even though mirroring is a complex phenomenon, in this study, we focus on the detection of head-nodding as a simple non-verbal communication cue due to its significance as a gesture displayed during social interactions. This paper introduces a computer vision-based method to detect mirroring through the analysis of head gestures using wearable cameras (smart glasses). In addition, we study how such a method can be used to explore perceived competence. The proposed method has been evaluated and the experiments demonstrate how static and wearable cameras seem to be equally effective to gather the information required for the analysis.  
  Address Santiago de Chile; December 2015  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference ICCVW  
  Notes OR; 600.068; 600.072;MV Approved no  
  Call Number (up) Admin @ si @ TRM2015 Serial 2722  
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Author Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza de Luna; Joaquin Salas edit   pdf
doi  openurl
  Title Head-gestures mirroring detection in dyadic social linteractions with computer vision-based wearable devices Type Journal Article
  Year 2016 Publication Neurocomputing Abbreviated Journal NEUCOM  
  Volume 175 Issue B Pages 866–876  
  Keywords Head gestures recognition; Mirroring detection; Dyadic social interaction analysis; Wearable devices  
  Abstract During face-to-face human interaction, nonverbal communication plays a fundamental role. A relevant aspect that takes part during social interactions is represented by mirroring, in which a person tends to mimic the non-verbal behavior (head and body gestures, vocal prosody, etc.) of the counterpart. In this paper, we introduce a computer vision-based system to detect mirroring in dyadic social interactions with the use of a wearable platform. In our context, mirroring is inferred as simultaneous head noddings displayed by the interlocutors. Our approach consists of the following steps: (1) facial features extraction; (2) facial features stabilization; (3) head nodding recognition; and (4) mirroring detection. Our system achieves a mirroring detection accuracy of 72% on a custom mirroring dataset.  
  Address  
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  Notes OR; 600.072; 600.068;MV Approved no  
  Call Number (up) Admin @ si @ TRM2016 Serial 2721  
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