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Author Yaxing Wang; Chenshen Wu; Luis Herranz; Joost Van de Weijer; Abel Gonzalez-Garcia; Bogdan Raducanu
Title Transferring GANs: generating images from limited data Type Conference Article
Year 2018 Publication 15th European Conference on Computer Vision Abbreviated Journal
Volume 11210 Issue Pages (up) 220-236
Keywords Generative adversarial networks; Transfer learning; Domain adaptation; Image generation
Abstract ransferring knowledge of pre-trained networks to new domains by means of fine-tuning is a widely used practice for applications based on discriminative models. To the best of our knowledge this practice has not been studied within the context of generative deep networks. Therefore, we study domain adaptation applied to image generation with generative adversarial networks. We evaluate several aspects of domain adaptation, including the impact of target domain size, the relative distance between source and target domain, and the initialization of conditional GANs. Our results show that using knowledge from pre-trained networks can shorten the convergence time and can significantly improve the quality of the generated images, especially when target data is limited. We show that these conclusions can also be drawn for conditional GANs even when the pre-trained model was trained without conditioning. Our results also suggest that density is more important than diversity and a dataset with one or few densely sampled classes is a better source model than more diverse datasets such as ImageNet or Places.
Address Munich; September 2018
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 ECCV
Notes LAMP; 600.109; 600.106; 600.120 Approved no
Call Number Admin @ si @ WWH2018a Serial 3130
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Author Lluis Pere de las Heras; Ahmed Sheraz; Marcus Liwicki; Ernest Valveny; Gemma Sanchez
Title Statistical Segmentation and Structural Recognition for Floor Plan Interpretation Type Journal Article
Year 2014 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 17 Issue 3 Pages (up) 221-237
Keywords
Abstract A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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; ADAS; 600.076; 600.077 Approved no
Call Number HSL2014 Serial 2370
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Author Laura Igual; Joan Carles Soliva; Roger Gimeno; Sergio Escalera; Oscar Vilarroya; Petia Radeva
Title Automatic Internal Segmentation of Caudate Nucleus for Diagnosis of Attention Deficit Hyperactivity Disorder Type Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7325 Issue II Pages (up) 222-229
Keywords
Abstract Poster
Studies on volumetric brain Magnetic Resonance Imaging (MRI) showed neuroanatomical abnormalities in pediatric Attention-Deficit/Hyperactivity Disorder (ADHD). In particular, the diminished right caudate volume is one of the most replicated findings among ADHD samples in morphometric MRI studies. In this paper, we propose a fully-automatic method for internal caudate nucleus segmentation based on machine learning. Moreover, the ratio between right caudate body volume and the bilateral caudate body volume is applied in a ADHD diagnostic test. We separately validate the automatic internal segmentation of caudate in head and body structures and the diagnostic test using real data from ADHD and control subjects. As a result, we show accurate internal caudate segmentation and similar performance among the proposed automatic diagnostic test and the manual annotation.
Address Aveiro, Portugal
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 0302-9743 ISBN 978-3-642-31297-7 Medium
Area Expedition Conference ICIAR
Notes OR; HuPBA; MILAB Approved no
Call Number Admin @ si @ ISG2012 Serial 2059
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Author Cristina Sanchez Montes; Jorge Bernal; Ana Garcia Rodriguez; Henry Cordova; Gloria Fernandez Esparrach
Title Revisión de métodos computacionales de detección y clasificación de pólipos en imagen de colonoscopia Type Journal Article
Year 2020 Publication Gastroenterología y Hepatología Abbreviated Journal GH
Volume 43 Issue 4 Pages (up) 222-232
Keywords
Abstract Computer-aided diagnosis (CAD) is a tool with great potential to help endoscopists in the tasks of detecting and histologically classifying colorectal polyps. In recent years, different technologies have been described and their potential utility has been increasingly evidenced, which has generated great expectations among scientific societies. However, most of these works are retrospective and use images of different quality and characteristics which are analysed off line. This review aims to familiarise gastroenterologists with computational methods and the particularities of endoscopic imaging, which have an impact on image processing analysis. Finally, the publicly available image databases, needed to compare and confirm the results obtained with different methods, are presented.
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
Notes MV; Approved no
Call Number Admin @ si @ SBG2020 Serial 3404
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Author F. Pla; Petia Radeva; Jordi Vitria
Title Non-parametric distance-based classification techniques and their applications Type Journal
Year 2008 Publication Pattern Analysis and Applications, Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications Abbreviated Journal
Volume 11 Issue 3-4 Pages (up) 223–225
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Springer 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;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ PRV2008 Serial 999
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Author Jaume Gibert; Ernest Valveny
Title Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. Type Conference Article
Year 2010 Publication 13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition Abbreviated Journal
Volume 6218 Issue Pages (up) 223–232
Keywords
Abstract Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano,
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-14979-5 Medium
Area Expedition Conference S+SSPR
Notes DAG Approved no
Call Number DAG @ dag @ GiV2010 Serial 1416
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Author Carolina Malagelada; F.De Lorio; Santiago Segui; S. Mendez; Michal Drozdzal; Jordi Vitria; Petia Radeva; J.Santos; Anna Accarino; Juan R. Malagelada; Fernando Azpiroz
Title Functional gut disorders or disordered gut function? Small bowel dysmotility evidenced by an original technique Type Journal Article
Year 2012 Publication Neurogastroenterology & Motility Abbreviated Journal NEUMOT
Volume 24 Issue 3 Pages (up) 223-230
Keywords capsule endoscopy;computer vision analysis;machine learning technique;small bowel motility
Abstract JCR Impact Factor 2010: 3.349
Background This study aimed to determine the proportion of cases with abnormal intestinal motility among patients with functional bowel disorders. To this end, we applied an original method, previously developed in our laboratory, for analysis of endoluminal images obtained by capsule endoscopy. This novel technology is based on computer vision and machine learning techniques.
 Methods The endoscopic capsule (Pillcam SB1; Given Imaging, Yokneam, Israel) was administered to 80 patients with functional bowel disorders and 70 healthy subjects. Endoluminal image analysis was performed with a computer vision program developed for the evaluation of contractile events (luminal occlusions and radial wrinkles), non-contractile patterns (open tunnel and smooth wall patterns), type of content (secretions, chyme) and motion of wall and contents. Normality range and discrimination of abnormal cases were established by a machine learning technique. Specifically, an iterative classifier (one-class support vector machine) was applied in a random population of 50 healthy subjects as a training set and the remaining subjects (20 healthy subjects and 80 patients) as a test set.
 Key Results The classifier identified as abnormal 29% of patients with functional diseases of the bowel (23 of 80), and as normal 97% of healthy subjects (68 of 70) (P < 0.05 by chi-squared test). Patients identified as abnormal clustered in two groups, which exhibited either a hyper- or a hypodynamic motility pattern. The motor behavior was unrelated to clinical features.
Conclusions &  Inferences With appropriate methodology, abnormal intestinal motility can be demonstrated in a significant proportion of patients with functional bowel disorders, implying a pathologic disturbance of gut physiology.
Address
Corporate Author Thesis
Publisher Wiley Online Library 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 MILAB; OR; MV Approved no
Call Number Admin @ si @ MLS2012 Serial 1830
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Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester
Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Book Chapter
Year 2012 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal
Volume 7029 Issue Pages (up) 223–230
Keywords medial manifolds, abdomen.
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 Toronto; Canada;
Corporate Author Thesis
Publisher Springer Link Place of Publication Berlin Editor H. Yoshida et al
Language English Summary Language English Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-28556-1 Medium
Area Expedition Conference ABDI
Notes IAM;MV Approved no
Call Number IAM @ iam @ VGB2012 Serial 1834
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Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru
Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Conference Article
Year 2011 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal
Volume 7029 Issue Pages (up) 223-230
Keywords
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 Nice, France
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor In H. Yoshida et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ABDI
Notes IAM; MV Approved no
Call Number VGB2011 Serial 2036
Permanent link to this record
 
 
Author Jorge Bernal; Fernando Vilariño; F. Javier Sanchez; M. Arnold; Anarta Ghosh; Gerard Lacey
Title Experts vs Novices: Applying Eye-tracking Methodologies in Colonoscopy Video Screening for Polyp Search Type Conference Article
Year 2014 Publication 2014 Symposium on Eye Tracking Research and Applications Abbreviated Journal
Volume Issue Pages (up) 223-226
Keywords
Abstract We present in this paper a novel study aiming at identifying the differences in visual search patterns between physicians of diverse levels of expertise during the screening of colonoscopy videos. Physicians were clustered into two groups -experts and novices- according to the number of procedures performed, and fixations were captured by an eye-tracker device during the task of polyp search in different video sequences. These fixations were integrated into heat maps, one for each cluster. The obtained maps were validated over a ground truth consisting of a mask of the polyp, and the comparison between experts and novices was performed by using metrics such as reaction time, dwelling time and energy concentration ratio. Experimental results show a statistically significant difference between experts and novices, and the obtained maps show to be a useful tool for the characterisation of the behaviour of each group.
Address USA; March 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 978-1-4503-2751-0 Medium
Area Expedition Conference ETRA
Notes MV; 600.047; 600.060;SIAI Approved no
Call Number Admin @ si @ BVS2014 Serial 2448
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Author David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados
Title A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting Type Journal Article
Year 2015 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 18 Issue 3 Pages (up) 223-234
Keywords Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation
Abstract The Bag-of-Visual-Words (BoVW) framework has gained popularity among the document image analysis community, specifically as a representation of handwritten words for recognition or spotting purposes. Although in the computer vision field the BoVW method has been greatly improved, most of the approaches in the document image analysis domain still rely on the basic implementation of the BoVW method disregarding such latest refinements. In this paper, we present a review of those improvements and its application to the keyword spotting task. We thoroughly evaluate their impact against a baseline system in the well-known George Washington dataset and compare the obtained results against nine state-of-the-art keyword spotting methods. In addition, we also compare both the baseline and improved systems with the methods presented at the Handwritten Keyword Spotting Competition 2014.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 Approved no
Call Number Admin @ si @ ART2015 Serial 2679
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Author David Aldavert; Marçal Rusiñol
Title Synthetically generated semantic codebook for Bag-of-Visual-Words based word spotting Type Conference Article
Year 2018 Publication 13th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages (up) 223 - 228
Keywords Word Spotting; Bag of Visual Words; Synthetic Codebook; Semantic Information
Abstract Word-spotting methods based on the Bag-ofVisual-Words framework have demonstrated a good retrieval performance even when used in a completely unsupervised manner. Although unsupervised approaches are suitable for
large document collections due to the cost of acquiring labeled data, these methods also present some drawbacks. For instance, having to train a suitable “codebook” for a certain dataset has a high computational cost. Therefore, in
this paper we present a database agnostic codebook which is trained from synthetic data. The aim of the proposed approach is to generate a codebook where the only information required is the type of script used in the document. The use of synthetic data also allows to easily incorporate semantic
information in the codebook generation. So, the proposed method is able to determine which set of codewords have a semantic representation of the descriptor feature space. Experimental results show that the resulting codebook attains a state-of-the-art performance while having a more compact representation.
Address Viena; Austria; April 2018
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; 600.084; 600.129; 600.121 Approved no
Call Number Admin @ si @ AlR2018b Serial 3105
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Author C. Alejandro Parraga; Xavier Otazu; Arash Akbarinia
Title Modelling symmetry perception with banks of quadrature convolutional Gabor kernels Type Conference Article
Year 2019 Publication 42nd edition of the European Conference on Visual Perception Abbreviated Journal
Volume Issue Pages (up) 224-224
Keywords
Abstract Mirror symmetry is a property most likely to be encountered in animals than in medium scale vegetation or inanimate objects in the natural world. This might be the reason why the human visual system has evolved to detect it quickly and robustly. Indeed, the perception of symmetry assists higher-level visual processing that are crucial for survival such as target recognition and identification irrespective of position and location. Although the task of detecting symmetrical objects seems effortless to us, it is very challenging for computers (to the extent that it has been proposed as a robust “captcha” by Funk & Liu in 2016). Indeed, the exact mechanism of symmetry detection in primates is not well understood: fMRI studies have shown that symmetrical shapes activate specific higher-level areas of the visual cortex (Sasaki et al.; 2005) and similarly, a large body of psychophysical experiments suggest that the symmetry perception is critically influenced by low-level mechanisms (Treder; 2010). In this work we attempt to find plausible low-level mechanisms that might form the basis for symmetry perception. Our simple model is made from banks of (i) odd-symmetric Gabors (resembling edge-detecting V1 neurons); and (ii) banks of larger odd- and even-symmetric Gabors (resembling higher visual cortex neurons), that pool signals from the 'edge image'. As reported previously (Akbarinia et al, ECVP2017), the convolution of the symmetrical lines with the two Gabor kernels of alternative phase produces a minimum in one and a maximum in the other (Osorio; 1996), and the rectification and combination of these signals create lines which hint of mirror symmetry in natural images. We improved the algorithm by combining these signals across several spatial scales. Our preliminary results suggest that such multiscale combination of convolutional operations might form the basis for much of the operation of the HVS in terms of symmetry detection and representation.
Address Leuven; Belgium; August 2019
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 ECVP
Notes NEUROBIT; 600.128 Approved no
Call Number Admin @ si @ POA2019 Serial 3371
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Author Josep Llados; Jaime Lopez-Krahe; Gemma Sanchez; Enric Marti
Title Interprétation de cartes et plans par mise en correspondance de graphes de attributs Type Conference Article
Year 2000 Publication 12 Congrès Francophone AFRIF–AFIA Abbreviated Journal
Volume 3 Issue Pages (up) 225-234
Keywords
Abstract
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 RFIA
Notes DAG;IAM Approved no
Call Number IAM @ iam @ LLS2000 Serial 1567
Permanent link to this record
 
 
Author Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta
Title Robust and accurate diaphragm border detection in cardiac X-Ray angiographies Type Conference Article
Year 2012 Publication Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges Abbreviated Journal
Volume 7746 Issue Pages (up) 225-234
Keywords
Abstract Workshop STACOM, dins del MICCAI
X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods.
Address Nice, France
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 0302-9743 ISBN 978-3-642-36960-5 Medium
Area Expedition Conference STACOM
Notes MILAB Approved no
Call Number Admin @ si @ PRC2012 Serial 2028
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