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Author Tadashi Araki; Nobutaka Ikeda; Nilanjan Dey; Sayan Chakraborty; Luca Saba; Dinesh Kumar; Elisa Cuadrado Godia; Xiaoyi Jiang; Ajay Gupta; Petia Radeva; John R. Laird; Andrew Nicolaides; Jasjit S. Suri
Title (down) A comparative approach of four different image registration techniques for quantitative assessment of coronary artery calcium lesions using intravascular ultrasound Type Journal Article
Year 2015 Publication Computer Methods and Programs in Biomedicine Abbreviated Journal CMPB
Volume 118 Issue 2 Pages 158-172
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Address
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Notes MILAB Approved no
Call Number Admin @ si @ AID2015 Serial 2640
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Author Javier Vazquez; G. D. Finlayson; Maria Vanrell
Title (down) 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 Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke
Title (down) A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores Type Journal Article
Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 13 Issue 4 Pages 243-259
Keywords
Abstract The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers.
Address
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 1433-2833 ISBN Medium
Area Expedition Conference
Notes DAG; CAT;CIC Approved no
Call Number FLS2010b Serial 1319
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Author Javier Vazquez; Maria Vanrell; Anna Salvatella; Eduard Vazquez
Title (down) A colour space based on the image content Type Book Chapter
Year 2007 Publication Artificial Intelligence Research and Development, C. Angulo and L. Godo, pp 205–212 IOS Press Abbreviated Journal
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Address
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Notes CIC Approved no
Call Number CAT @ cat @ VVS2007 Serial 829
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Author Robert Benavente; Maria Vanrell
Title (down) A colour naming experiment Type Report
Year 2001 Publication CVC Technical Report #56 Abbreviated Journal
Volume Issue Pages
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Abstract
Address CVC (UAB)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ BeV2001 Serial 78
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Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes
Title (down) 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 Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny
Title (down) 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
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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 Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez
Title (down) 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
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Address Colorado Springs; USA
Corporate Author Thesis
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Area Expedition Conference CVPR
Notes ISE Approved no
Call Number Admin @ si @ PVG2011 Serial 1764
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Author Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez; Xavier Roca
Title (down) A coarse-to-fine approach for fast deformable object detection Type Journal Article
Year 2015 Publication Pattern Recognition Abbreviated Journal PR
Volume 48 Issue 5 Pages 1844-1853
Keywords
Abstract We present a method that can dramatically accelerate object detection with part based models. The method is based on the observation that the cost of detection is likely to be dominated by the cost of matching each part to the image, and not by the cost of computing the optimal configuration of the parts as commonly assumed. Therefore accelerating detection requires minimizing the number of
part-to-image comparisons. To this end we propose a multiple-resolutions hierarchical part based model and a corresponding coarse-to-fine inference procedure that recursively eliminates from the search space unpromising part
placements. The method yields a ten-fold speedup over the standard dynamic programming approach and is complementary to the cascade-of-parts approach of [9]. Compared to the latter, our method does not have parameters to be determined empirically, which simplifies its use during the training of the model. Most importantly, the two techniques can be combined to obtain a very significant speedup, of two orders of magnitude in some cases. We evaluate our method extensively on the PASCAL VOC and INRIA datasets, demonstrating a very high increase in the detection speed with little degradation of the accuracy.
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Notes ISE; 600.078; 602.005; 605.001; 302.012 Approved no
Call Number Admin @ si @ PVG2015 Serial 2628
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Author Diego Velazquez; Pau Rodriguez; Josep M. Gonfaus; Xavier Roca; Jordi Gonzalez
Title (down) A Closer Look at Embedding Propagation for Manifold Smoothing Type Journal Article
Year 2022 Publication Journal of Machine Learning Research Abbreviated Journal JMLR
Volume 23 Issue 252 Pages 1-27
Keywords Regularization; emi-supervised learning; self-supervised learning; adversarial robustness; few-shot classification
Abstract Supervised training of neural networks requires a large amount of manually annotated data and the resulting networks tend to be sensitive to out-of-distribution (OOD) data.
Self- and semi-supervised training schemes reduce the amount of annotated data required during the training process. However, OOD generalization remains a major challenge for most methods. Strategies that promote smoother decision boundaries play an important role in out-of-distribution generalization. For example, embedding propagation (EP) for manifold smoothing has recently shown to considerably improve the OOD performance for few-shot classification. EP achieves smoother class manifolds by building a graph from sample embeddings and propagating information through the nodes in an unsupervised manner. In this work, we extend the original EP paper providing additional evidence and experiments showing that it attains smoother class embedding manifolds and improves results in settings beyond few-shot classification. Concretely, we show that EP improves the robustness of neural networks against multiple adversarial attacks as well as semi- and
self-supervised learning performance.
Address 9/2022
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Notes Approved no
Call Number Admin @ si @ VRG2022 Serial 3762
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Author Lubomir Latchev; Maya Dimitrova; David Rotger
Title (down) A Classifier of Technical Diagnostic States of Electrocardiograph Type Miscellaneous
Year 2006 Publication International Conference on Computer Systems and Technologies (CompSysTech´06), 15.1–15.6 Abbreviated Journal
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Address University of Veliko Tarnovo (Bulgaria)
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Notes Approved no
Call Number Admin @ si @ LDR2006 Serial 774
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Author Onur Ferhat; Fernando Vilariño; F. Javier Sanchez
Title (down) A cheap portable eye-tracker solution for common setups. Type Journal Article
Year 2014 Publication Journal of Eye Movement Research Abbreviated Journal JEMR
Volume 7 Issue 3 Pages 1-10
Keywords
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 which can work on a computer with 30Hz sampling rate. After assessing the accuracy of our eye-tracker in elaborated experiments involving 12 subjects under 4 different system setups, we install it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.42° horizontal accuracy with 3Hz refresh rate for a building cost of 70 Euros.
Address
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Area Expedition Conference
Notes ;SIAI Approved no
Call Number Admin @ si @ FVS2014 Serial 2435
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Author Onur Ferhat; Fernando Vilariño
Title (down) 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
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Publisher Place of Publication Editor
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ISSN ISBN Medium
Area Expedition Conference ECEM
Notes MV;SIAI Approved no
Call Number Admin @ si @ FeV2013 Serial 2374
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
Title (down) 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
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Address Angers, France
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Publisher ICEIS Press Place of Publication Editor
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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 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 (down) 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
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ISSN ISBN Medium
Area Expedition Conference ICML
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ GCE2016 Serial 2769
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