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| Author | Josep Llados; Enric Marti | ||||
| Title | A graph-edit algorithm for hand-drawn graphical document recognition and their automatic introduction into CAD systems | Type | Journal Article | ||
| Year | 1999 | Publication | Machine Graphics & Vision | Abbreviated Journal | |
| Volume | 8 | Issue | Pages  |
195-211 | |
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| Area | Expedition | Conference | |||
| Notes | DAG;IAM; | Approved | no | ||
| Call Number | IAM @ iam @ LIM1999 | Serial | 1568 | ||
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| Author | Andreas Fischer; Ching Y. Suen; Volkmar Frinken; Kaspar Riesen; Horst Bunke | ||||
| Title | A Fast Matching Algorithm for Graph-Based Handwriting Recognition | Type | Conference Article | ||
| Year | 2013 | Publication | 9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition | Abbreviated Journal | |
| Volume | 7877 | Issue | Pages |
194-203 | |
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| Abstract | The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. This approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. The time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy. | ||||
| Address | Vienna; Austria; May 2013 | ||||
| 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 | 978-3-642-38220-8 | Medium | |
| Area | Expedition | Conference | GBR | ||
| Notes | DAG; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ FSF2013 | Serial | 2294 | ||
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| Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
| Title | Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 220 | Issue | Pages |
193–200 | |
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| Abstract | Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships. | ||||
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| Publisher | Place of Publication | Editor | R. Alquezar, A. Moreno, J. Aguilar | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-642-3 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PEP2010 | Serial | 1448 | ||
| Permanent link to this record | |||||
| Author | Ernest Valveny; Enric Marti | ||||
| Title | Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition | Type | Journal Article | ||
| Year | 2000 | Publication | Graphics Recognition Recent Advances | Abbreviated Journal | |
| Volume | 1941 | Issue | Pages |
193-208 | |
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| Abstract | We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols. | ||||
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| Corporate Author | Springer Verlag | Thesis | |||
| Publisher | Springer Verlag | Place of Publication | Editor | ||
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| Area | Expedition | Conference | |||
| Notes | DAG;IAM; | Approved | no | ||
| Call Number | IAM @ iam @ MVA2000 | Serial | 1655 | ||
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| Author | Petia Radeva; A.Amini; J.Huang; Enric Marti | ||||
| Title | Deformable B-Solids and Implicit Snakes for Localization and Tracking of SPAMM MRI-Data | Type | Conference Article | ||
| Year | 1996 | Publication | Workshop on Mathematical Methods in Biomedical Image Analysis | Abbreviated Journal | |
| Volume | Issue | Pages |
192-201 | ||
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| Abstract | To date, MRI-SPAMM data from different image slices have been analyzed independently. In this paper, we propose an approach for 3D tag localization and tracking of SPAMM data by a novel deformable B-solid. The solid is defined in terms of a 3D tensor product B-spline. The isoparametric curves of the B-spline solid have special importance. These are termed implicit snakes as they deform under image forces from tag lines in different image slices. The localization and tracking of tag lines is performed under constraints of continuity and smoothness of the B-solid. The framework unifies the problems of localization, and displacement fitting and interpolation into the same procedure utilizing B-spline bases for interpolation. To track motion from boundaries and restrict image forces to the myocardium, a volumetric model is employed as a pair of coupled endocardial and epicardial B-spline surfaces. To recover deformations in the LV an energy-minimization problem is posed where both tag and ... | ||||
| Address | San Francisco CA | ||||
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| Publisher | IEEE Computer Society | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 0-8186-7368-0 | Medium | ||
| Area | Expedition | Conference | MMBIA ’96 | ||
| Notes | MILAB;IAM; | Approved | no | ||
| Call Number | IAM @ iam @ RAH1996 | Serial | 1630 | ||
| Permanent link to this record | |||||
| Author | Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio | ||||
| Title | Automatic Tumor Volume Segmentation in Whole-Body PET/CT Scans: A Supervised Learning Approach Source | Type | Journal Article | ||
| Year | 2015 | Publication | Journal of Medical Imaging and Health Informatics | Abbreviated Journal | JMIHI |
| Volume | 5 | Issue | 2 | Pages |
192-201 |
| Keywords | CONTEXTUAL CLASSIFICATION; PET/CT; SUPERVISED LEARNING; TUMOR SEGMENTATION; WHOLE BODY | ||||
| Abstract | Whole-body 3D PET/CT tumoral volume segmentation provides relevant diagnostic and prognostic information in clinical oncology and nuclear medicine. Carrying out this procedure manually by a medical expert is time consuming and suffers from inter- and intra-observer variabilities. In this paper, a completely automatic approach to this task is presented. First, the problem is stated and described both in clinical and technological terms. Then, a novel supervised learning segmentation framework is introduced. The segmentation by learning approach is defined within a Cascade of Adaboost classifiers and a 3D contextual proposal of Multiscale Stacked Sequential Learning. Segmentation accuracy results on 200 Breast Cancer whole body PET/CT volumes show mean 49% sensitivity, 99.993% specificity and 39% Jaccard overlap Index, which represent good performance results both at the clinical and technological level. | ||||
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| Area | Expedition | Conference | |||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SED2015 | Serial | 2584 | ||
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| Author | R. Clariso; David Masip; A. Rius | ||||
| Title | Student projects empowering mobile learning in higher education | Type | Journal | ||
| Year | 2014 | Publication | Revista de Universidad y Sociedad del Conocimiento | Abbreviated Journal | RUSC |
| Volume | 11 | Issue | Pages |
192-207 | |
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1698-580X | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ CMR2014 | Serial | 2619 | ||
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| Author | Lluis Gomez; Dimosthenis Karatzas | ||||
| Title | A fine-grained approach to scene text script identification | Type | Conference Article | ||
| Year | 2016 | Publication | 12th IAPR Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages |
192-197 | ||
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| Abstract | This paper focuses on the problem of script identification in unconstrained scenarios. Script identification is an important prerequisite to recognition, and an indispensable condition for automatic text understanding systems designed for multi-language environments. Although widely studied for document images and handwritten documents, it remains an almost unexplored territory for scene text images. We detail a novel method for script identification in natural images that combines convolutional features and the Naive-Bayes Nearest Neighbor classifier. The proposed framework efficiently exploits the discriminative power of small stroke-parts, in a fine-grained classification framework. In addition, we propose a new public benchmark dataset for the evaluation of joint text detection and script identification in natural scenes. Experiments done in this new dataset demonstrate that the proposed method yields state of the art results, while it generalizes well to different datasets and variable number of scripts. The evidence provided shows that multi-lingual scene text recognition in the wild is a viable proposition. Source code of the proposed method is made available online. | ||||
| Address | Santorini; Grecia; April 2016 | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG; 601.197; 600.084 | Approved | no | ||
| Call Number | Admin @ si @ GoK2016b | Serial | 2863 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
| Title | Query Driven Word Retrieval in Graphical Documents | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages |
191–198 | ||
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| Abstract | In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. | ||||
| Address | Boston; USA | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60558-773-8 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPL2010b | Serial | 1433 | ||
| Permanent link to this record | |||||
| Author | T.O. Nguyen; Salvatore Tabbone; Oriol Ramos Terrades | ||||
| Title | Symbol Descriptor Based on Shape Context and Vector Model of Information Retrieval | Type | Conference Article | ||
| Year | 2008 | Publication | Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, | Abbreviated Journal | |
| Volume | Issue | Pages |
191-197 | ||
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| Address | Nara, Japan | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ NTR2008a | Serial | 1873 | ||
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| Author | Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez | ||||
| Title | GTCreator: a flexible annotation tool for image-based datasets | Type | Journal Article | ||
| Year | 2019 | Publication | International Journal of Computer Assisted Radiology and Surgery | Abbreviated Journal | IJCAR |
| Volume | 14 | Issue | 2 | Pages |
191–201 |
| Keywords | Annotation tool; Validation Framework; Benchmark; Colonoscopy; Evaluation | ||||
| Abstract | Abstract Purpose: Methodology evaluation for decision support systems for health is a time consuming-task. To assess performance of polyp detection
methods in colonoscopy videos, clinicians have to deal with the annotation of thousands of images. Current existing tools could be improved in terms of exibility and ease of use. Methods:We introduce GTCreator, a exible annotation tool for providing image and text annotations to image-based datasets. It keeps the main basic functionalities of other similar tools while extending other capabilities such as allowing multiple annotators to work simultaneously on the same task or enhanced dataset browsing and easy annotation transfer aiming to speed up annotation processes in large datasets. Results: The comparison with other similar tools shows that GTCreator allows to obtain fast and precise annotation of image datasets, being the only one which offers full annotation editing and browsing capabilites. Conclusions: Our proposed annotation tool has been proven to be efficient for large image dataset annota- tion, as well as showing potential of use in other stages of method evaluation such as experimental setup or results analysis. |
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| Area | Expedition | Conference | |||
| Notes | MV; 600.096; 600.109; 600.119; 601.305 | Approved | no | ||
| Call Number | Admin @ si @ BHM2019 | Serial | 3163 | ||
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| Author | David Geronimo; Angel Sappa; Antonio Lopez | ||||
| Title | Stereo-based Candidate Generation for Pedestrian Protection Systems | Type | Book Chapter | ||
| Year | 2010 | Publication | Binocular Vision: Development, Depth Perception and Disorders | Abbreviated Journal | |
| Volume | Issue | 9 | Pages |
189–208 | |
| Keywords | Pedestrian Detection | ||||
| Abstract | This chapter describes a stereo-based algorithm that provides candidate image windows to a latter 2D classification stage in an on-board pedestrian detection system. The proposed algorithm, which consists of three stages, is based on the use of both stereo imaging and scene prior knowledge (i.e., pedestrians are on the ground) to reduce the candidate searching space. First, a successful road surface fitting algorithm provides estimates on the relative ground-camera pose. This stage directs the search toward the road area thus avoiding irrelevant regions like the sky. Then, three different schemes are used to scan the estimated road surface with pedestrian-sized windows: (a) uniformly distributed through the road surface (3D); (b) uniformly distributed through the image (2D); (c) not uniformly distributed but according to a quadratic function (combined 2D-3D). Finally, the set of candidate windows is reduced by analyzing their 3D content. Experimental results of the proposed algorithm, together with statistics of searching space reduction are provided. | ||||
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| Publisher | NOVA Publishers | Place of Publication | Editor | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ GSL2010 | Serial | 1301 | ||
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| Author | Patricia Suarez; Dario Carpio; Angel Sappa | ||||
| Title | Boosting Guided Super-Resolution Performance with Synthesized Images | Type | Conference Article | ||
| Year | 2023 | Publication | 17th International Conference on Signal-Image Technology & Internet-Based Systems | Abbreviated Journal | |
| Volume | Issue | Pages |
189-195 | ||
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| Abstract | Guided image processing techniques are widely used for extracting information from a guiding image to aid in the processing of the guided one. These images may be sourced from different modalities, such as 2D and 3D, or different spectral bands, like visible and infrared. In the case of guided cross-spectral super-resolution, features from the two modal images are extracted and efficiently merged to migrate guidance information from one image, usually high-resolution (HR), toward the guided one, usually low-resolution (LR). Different approaches have been recently proposed focusing on the development of architectures for feature extraction and merging in the cross-spectral domains, but none of them care about the different nature of the given images. This paper focuses on the specific problem of guided thermal image super-resolution, where an LR thermal image is enhanced by an HR visible spectrum image. To improve existing guided super-resolution techniques, a novel scheme is proposed that maps the original guiding information to a thermal image-like representation that is similar to the output. Experimental results evaluating five different approaches demonstrate that the best results are achieved when the guiding and guided images share the same domain. | ||||
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| Area | Expedition | Conference | SITIS | ||
| Notes | MSIAU | Approved | no | ||
| Call Number | Admin @ si @ SCS2023c | Serial | 4011 | ||
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| Author | Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva | ||||
| Title | A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment | Type | Book Chapter | ||
| Year | 2006 | Publication | 11th Iberoamerican Congress on Pattern Recognition | Abbreviated Journal | |
| Volume | 4225 | Issue | Pages |
188–197 | |
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| Abstract | Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment. | ||||
| Address | Cancun (Mexico) | ||||
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| Publisher | Springer Verlag | Place of Publication | Berlin-Heidelberg | Editor | J.P. Martinez–Trinidad et al |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | 800 | Expedition | Conference | CIARP06 | |
| Notes | MV;OR;MILAB;SIAI | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e | Serial | 729 | ||
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| Author | Jose Antonio Rodriguez; Florent Perronnin | ||||
| Title | Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents | Type | Book Chapter | ||
| Year | 2008 | Publication | Graphics Recognition: Recent Advances and New Opportunities | Abbreviated Journal | |
| Volume | 5046 | Issue | Pages |
188–198 | |
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| Publisher | Place of Publication | Editor | W. Liu, J. Llados, J.M. Ogier | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | Admin @ si @ RoP2008a | Serial | 992 | ||
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