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Author David Vazquez; Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Antonio Lopez; Adriana Romero; Michal Drozdzal; Aaron Courville
Title (up) A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images Type Conference Article
Year 2017 Publication 31st International Congress and Exhibition on Computer Assisted Radiology and Surgery Abbreviated Journal
Volume Issue Pages
Keywords Deep Learning; Medical Imaging
Abstract Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss-rate and inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing Decision Support Systems (DSS) aiming to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. We provide new baselines on this dataset by training standard fully convolutional networks (FCN) for semantic segmentation and significantly outperforming, without any further post-processing, prior results in endoluminal scene segmentation.
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 CARS
Notes ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 Approved no
Call Number ADAS @ adas @ VBS2017a Serial 2880
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Author Alicia Fornes; Josep Llados; Joan Mas; Joana Maria Pujadas-Mora; Anna Cabre
Title (up) A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts Type Conference Article
Year 2014 Publication Digital Access to Textual Cultural Heritage Conference Abbreviated Journal
Volume Issue Pages 103-108
Keywords
Abstract In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts.
Address Madrid; May 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 978-1-4503-2588-2 Medium
Area Expedition Conference DATeCH
Notes DAG; 600.061; 602.006; 600.077 Approved no
Call Number Admin @ si @ FLM2014 Serial 2516
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Author Isabelle Guyon; Imad Chaabane; Hugo Jair Escalante; Sergio Escalera; Damir Jajetic; James Robert Lloyd; Nuria Macia; Bisakha Ray; Lukasz Romaszko; Michele Sebag; Alexander Statnikov; Sebastien Treguer; Evelyne Viegas
Title (up) A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention Type Conference Article
Year 2016 Publication AutoML Workshop Abbreviated Journal
Volume Issue 1 Pages 1-8
Keywords AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning
Abstract The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems. The test bed was composed of 30 data sets from a wide variety of application domains and ranged across different types of complexity. Over six rounds, participants succeeded in delivering AutoML software capable of being trained and tested without human intervention. Although improvements can still be made to close the gap between human-tweaked and AutoML models, this competition contributes to the development of fully automated environments by challenging practitioners to solve problems under specific constraints and sharing their approaches; the platform will remain available for post-challenge submissions at http://codalab.org/AutoML.
Address New York; USA; June 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 ICML
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ GCE2016 Serial 2769
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
Title (up) A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa Type Conference Article
Year 2003 Publication Proceedings of Pattern Recognition in Information Systems Abbreviated Journal
Volume Issue Pages 1-13
Keywords
Abstract
Address Angers, France
Corporate Author Thesis
Publisher ICEIS Press Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 972-98816-3-4 Medium
Area Expedition Conference PRIS'03
Notes DAG;IAM; Approved no
Call Number IAM @ iam @ LVS2003 Serial 1576
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Author Onur Ferhat; Fernando Vilariño
Title (up) A Cheap Portable Eye-Tracker Solution for Common Setups Type Conference Article
Year 2013 Publication 17th European Conference on Eye Movements Abbreviated Journal
Volume Issue Pages
Keywords Low cost; eye-tracker; software; webcam; Raspberry Pi
Abstract We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system. After assessing the accuracy of our eye-tracker in elaborated experiments involving 18 subjects under 4 different system setups, we developed a simple game to see how it performs in practice and we also installed it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.62° horizontal accuracy with 3 fps refresh rate for a building cost of 70 Euros.
Address Lund; Sweden; August 2013
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 ECEM
Notes MV;SIAI Approved no
Call Number Admin @ si @ FeV2013 Serial 2374
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Author Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez
Title (up) A Coarse-to-fine Approach for fast Deformable Object Detection Type Conference Article
Year 2011 Publication IEEE conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 1353-1360
Keywords
Abstract
Address Colorado Springs; USA
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 CVPR
Notes ISE Approved no
Call Number Admin @ si @ PVG2011 Serial 1764
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Author Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny
Title (up) A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 453-458
Keywords
Abstract In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.
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 978-1-4673-2262-1 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number DAG @ dag @ AFF2012 Serial 1983
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Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes
Title (up) A Coarse-to-Fine Word Spotting Approach for Historical Handwritten Documents Based on Graph Embedding and Graph Edit Distance Type Conference Article
Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 3074 - 3079
Keywords word spotting; coarse-to-fine mechamism; graphbased representation; graph embedding; graph edit distance
Abstract Effective information retrieval on handwritten document images has always been a challenging task, especially historical ones. In the paper, we propose a coarse-to-fine handwritten word spotting approach based on graph representation. The presented model comprises both the topological and morphological signatures of the handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. Aiming at developing a practical and efficient word spotting approach for large-scale historical handwritten documents, a fast and coarse comparison is first applied to prune the regions that are not similar to the query based on the graph embedding methodology. Afterwards, the query and regions of interest are compared by graph edit distance based on the Dynamic Time Warping alignment. The proposed approach is evaluated on a public dataset containing 50 pages of historical marriage license records. The results show that the proposed approach achieves a compromise between efficiency and accuracy.
Address Stockholm; Sweden; August 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 1051-4651 ISBN Medium
Area Expedition Conference ICPR
Notes DAG; 600.061; 602.006; 600.077 Approved no
Call Number Admin @ si @ WEG2014a Serial 2515
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Author Javier Vazquez; G. D. Finlayson; Maria Vanrell
Title (up) A compact singularity function to predict WCS data and unique hues Type Conference Article
Year 2010 Publication 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science Abbreviated Journal
Volume Issue Pages 33–38
Keywords
Abstract Understanding how colour is used by the human vision system is a widely studied research field. The field, though quite advanced, still faces important unanswered questions. One of them is the explanation of the unique hues and the assignment of color names. This problem addresses the fact of different perceptual status for different colors.
Recently, Philipona and O'Regan have proposed a biological model that allows to extract the reflection properties of any surface independently of the lighting conditions. These invariant properties are the basis to compute a singularity index that predicts the asymmetries presented in unique hues and basic color categories psychophysical data, therefore is giving a further step in their explanation.

In this paper we build on their formulation and propose a new singularity index. This new formulation equally accounts for the location of the 4 peaks of the World colour survey and has two main advantages. First, it is a simple elegant numerical measure (the Philipona measurement is a rather cumbersome formula). Second, we develop a colour-based explanation for the measure.
Address Joensuu, Finland
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 9781617388897 Medium
Area Expedition Conference CGIV/MCS
Notes CIC Approved no
Call Number CAT @ cat @ VFV2010 Serial 1324
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Author Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier; Josep Llados
Title (up) A Comparative Study of Local Detectors and Descriptors for Mobile Document Classification Type Conference Article
Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal
Volume Issue Pages 596-600
Keywords
Abstract In this paper we conduct a comparative study of local key-point detectors and local descriptors for the specific task of mobile document classification. A classification architecture based on direct matching of local descriptors is used as baseline for the comparative study. A set of four different key-point
detectors and four different local descriptors are tested in all the possible combinations. The experiments are conducted in a database consisting of 30 model documents acquired on 6 different backgrounds, totaling more than 36.000 test images.
Address Nancy; France; August 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 ICDAR
Notes DAG; 600.084; 600.61; 601.223; 600.077 Approved no
Call Number Admin @ si @ RCO2015 Serial 2684
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Author David Guillamet; Jordi Vitria
Title (up) A Comparison of Local versus Global Color Histograms for Object Recognition. Type Conference Article
Year 2000 Publication 15 th International Conference on Pattern Recognition Abbreviated Journal
Volume 2 Issue Pages 422-425
Keywords
Abstract
Address Barcelona.
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 ICPR
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ GuV2000 b Serial 229
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Author Patricia Marquez;Debora Gil;Aura Hernandez-Sabate
Title (up) A Complete Confidence Framework for Optical Flow Type Conference Article
Year 2012 Publication 12th European Conference on Computer Vision – Workshops and Demonstrations Abbreviated Journal
Volume 7584 Issue 2 Pages 124-133
Keywords Optical flow, confidence measures, sparsification plots, error prediction plots
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Florence, Italy, October 7-13, 2012 Editor Andrea Fusiello, Vittorio Murino ,Rita Cucchiara
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-33867-0 Medium
Area Expedition Conference ECCVW
Notes IAM;ADAS; Approved no
Call Number IAM @ iam @ MGH2012b Serial 1991
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Author Partha Pratim Roy; Josep Llados; Umapada Pal
Title (up) A Complete System for Detection and Recognition of Text in Graphical Documents using Background Information Type Conference Article
Year 2009 Publication 5th International Conference on Computer Vision Theory and Applications Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Lisboa, Portugal
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 978-989-8111-69-2 Medium
Area Expedition Conference VISAPP
Notes DAG Approved no
Call Number DAG @ dag @ RLP2009 Serial 1238
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Author Albin Soutif; Antonio Carta; Andrea Cossu; Julio Hurtado; Hamed Hemati; Vincenzo Lomonaco; Joost Van de Weijer
Title (up) A Comprehensive Empirical Evaluation on Online Continual Learning Type Conference Article
Year 2023 Publication Visual Continual Learning (ICCV-W) Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Online continual learning aims to get closer to a live learning experience by learning directly on a stream of data with temporally shifting distribution and by storing a minimum amount of data from that stream. In this empirical evaluation, we evaluate various methods from the literature that tackle online continual learning. More specifically, we focus on the class-incremental setting in the context of image classification, where the learner must learn new classes incrementally from a stream of data. We compare these methods on the Split-CIFAR100 and Split-TinyImagenet benchmarks, and measure their average accuracy, forgetting, stability, and quality of the representations, to evaluate various aspects of the algorithm at the end but also during the whole training period. We find that most methods suffer from stability and underfitting issues. However, the learned representations are comparable to i.i.d. training under the same computational budget. No clear winner emerges from the results and basic experience replay, when properly tuned and implemented, is a very strong baseline. We release our modular and extensible codebase at this https URL based on the avalanche framework to reproduce our results and encourage future research.
Address Paris; France; October 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 ICCVW
Notes LAMP Approved no
Call Number Admin @ si @ SCC2023 Serial 3938
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Author Maria Oliver; Gloria Haro; Mariella Dimiccoli; Baptiste Mazin; Coloma Ballester
Title (up) A computational model of amodal completion Type Conference Article
Year 2016 Publication SIAM Conference on Imaging Science Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper presents a computational model to recover the most likely interpretation of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler's elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler's elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling.
Address Albuquerque; New Mexico; USA; 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 IS
Notes MILAB; 601.235 Approved no
Call Number Admin @ si @OHD2016a Serial 2788
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