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Author | Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez | ||||
Title | Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios | Type | Conference Article | ||
Year | 2009 | Publication | 12th International Conference on Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 1499 - 1506 | ||
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Abstract | Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering “a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions. | ||||
Address ![]() |
Kyoto, Japan | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1550-5499 | ISBN | 978-1-4244-4420-5 | Medium | |
Area | Expedition | Conference | ICCV | ||
Notes | Approved | no | |||
Call Number | ISE @ ise @ HHM2009 | Serial | 1213 | ||
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Author | Gemma Roig; Xavier Boix; Fernando De la Torre | ||||
Title | Optimal Feature Selection for Subspace Image Matching | Type | Conference Article | ||
Year | 2009 | Publication | 2nd IEEE International Workshop on Subspace Methods in conjunction | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Image matching has been a central research topic in computer vision over the last decades. Typical approaches to correspondence involve matching feature points between images. In this paper, we present a novel problem for establishing correspondences between a sparse set of image features and a previously learned subspace model. We formulate the matching task as an energy minimization, and jointly optimize over all possible feature assignments and parameters of the subspace model. This problem is in general NP-hard. We propose a convex relaxation approximation, and develop two optimization strategies: naïve gradient-descent and quadratic programming. Alternatively, we reformulate the optimization criterion as a sparse eigenvalue problem, and solve it using a recently proposed backward greedy algorithm. Experimental results on facial feature detection show that the quadratic programming solution provides better selection mechanism for relevant features. | ||||
Address ![]() |
Kyoto, Japan | ||||
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 | ICCV | ||
Notes | Approved | no | |||
Call Number | Admin @ si @ RBT2009 | Serial | 1233 | ||
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Author | Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria | ||||
Title | A new image centrality descriptor for wrinkle frame detection in WCE videos | Type | Conference Article | ||
Year | 2013 | Publication | 13th IAPR Conference on Machine Vision Applications | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Small bowel motility dysfunctions are a widespread functional disorder characterized by abdominal pain and altered bowel habits in the absence of specific and unique organic pathology. Current methods of diagnosis are complex and can only be conducted at some highly specialized referral centers. Wireless Video Capsule Endoscopy (WCE) could be an interesting diagnostic alternative that presents excellent clinical advantages, since it is non-invasive and can be conducted by non specialists. The purpose of this work is to present a new method for the detection of wrinkle frames in WCE, a critical characteristic to detect one of the main motility events: contractions. The method goes beyond the use of one of the classical image feature, the Histogram | ||||
Address ![]() |
Kyoto; Japan; May 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 | MVA | ||
Notes | OR; MILAB; 600.046;MV | Approved | no | ||
Call Number | Admin @ si @ SDZ2013 | Serial | 2239 | ||
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Author | Victor Borjas; Jordi Vitria; Petia Radeva | ||||
Title | Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments | Type | Conference Article | ||
Year | 2013 | Publication | 13th IAPR Conference on Machine Vision Applications | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87% of the false positives and therefore the overall precision of the detection
was increased signicantly. |
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Address ![]() |
Kyoto; Japan; May 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 | MVA | ||
Notes | OR; MILAB;MV | Approved | no | ||
Call Number | BVR2013 | Serial | 2238 | ||
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Author | Hana Jarraya; Oriol Ramos Terrades; Josep Llados | ||||
Title | Learning structural loss parameters on graph embedding applied on symbolic graphs | Type | Conference Article | ||
Year | 2017 | Publication | 12th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | We propose an amelioration of proposed Graph Embedding (GEM) method in previous work that takes advantages of structural pattern representation and the structured distortion. it models an Attributed Graph (AG) as a Probabilistic Graphical Model (PGM). Then, it learns the parameters of this PGM presented by a vector, as new signature of AG in a lower dimensional vectorial space. We focus to adapt the structured learning algorithm via 1_slack formulation with a suitable risk function, called Graph Edit Distance (GED). It defines the dissimilarity of the ground truth and predicted graph labels. It determines by the error tolerant graph matching using bipartite graph matching algorithm. We apply Structured Support Vector Machines (SSVM) to process classification task. During our experiments, we got our results on the GREC dataset. | ||||
Address ![]() |
Kyoto; Japan; November 2017 | ||||
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 | GREC | ||
Notes | DAG; 600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ JRL2017b | Serial | 3073 | ||
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Author | J. Chazalon; P. Gomez-Kramer; Jean-Christophe Burie; M.Coustaty; S.Eskenazi; Muhammad Muzzamil Luqman; Nibal Nayef; Marçal Rusiñol; N. Sidere; Jean-Marc Ogier | ||||
Title | SmartDoc 2017 Video Capture: Mobile Document Acquisition in Video Mode | Type | Conference Article | ||
Year | 2017 | Publication | 1st International Workshop on Open Services and Tools for Document Analysis | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | As mobile document acquisition using smartphones is getting more and more common, along with the continuous improvement of mobile devices (both in terms of computing power and image quality), we can wonder to which extent mobile phones can replace desktop scanners. Modern applications can cope with perspective distortion and normalize the contrast of a document page captured with a smartphone, and in some cases like bottle labels or posters, smartphones even have the advantage of allowing the acquisition of non-flat or large documents. However, several cases remain hard to handle, such as reflective documents (identity cards, badges, glossy magazine cover, etc.) or large documents for which some regions require an important amount of detail. This paper introduces the SmartDoc 2017 benchmark (named “SmartDoc Video Capture”), which aims at
assessing whether capturing documents using the video mode of a smartphone could solve those issues. The task under evaluation is both a stitching and a reconstruction problem, as the user can move the device over different parts of the document to capture details or try to erase highlights. The material released consists of a dataset, an evaluation method and the associated tool, a sample method, and the tools required to extend the dataset. All the components are released publicly under very permissive licenses, and we particularly cared about maximizing the ease of understanding, usage and improvement. |
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Address ![]() |
Kyoto; Japan; November 2017 | ||||
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-OST | ||
Notes | DAG; 600.084; 600.121 | Approved | no | ||
Call Number | Admin @ si @ CGB2017 | Serial | 2997 | ||
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Author | Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas | ||||
Title | LSDE: Levenshtein Space Deep Embedding for Query-by-string Word Spotting | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | n this paper we present the LSDE string representation and its application to handwritten word spotting. LSDE is a novel embedding approach for representing strings that learns a space in which distances between projected points are correlated with the Levenshtein edit distance between the original strings.
We show how such a representation produces a more semantically interpretable retrieval from the user’s perspective than other state of the art ones such as PHOC and DCToW. We also conduct a preliminary handwritten word spotting experiment on the George Washington dataset. |
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Address ![]() |
Kyoto; Japan; November 2017 | ||||
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; 600.121 | Approved | no | ||
Call Number | Admin @ si @ GRK2017 | Serial | 2999 | ||
Permanent link to this record | |||||
Author | E. Royer; J. Chazalon; Marçal Rusiñol; F. Bouchara | ||||
Title | Benchmarking Keypoint Filtering Approaches for Document Image Matching | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Best Poster Award.
Reducing the amount of keypoints used to index an image is particularly interesting to control processing time and memory usage in real-time document image matching applications, like augmented documents or smartphone applications. This paper benchmarks two keypoint selection methods on a task consisting of reducing keypoint sets extracted from document images, while preserving detection and segmentation accuracy. We first study the different forms of keypoint filtering, and we introduce the use of the CORE selection method on keypoints extracted from document images. Then, we extend a previously published benchmark by including evaluations of the new method, by adding the SURF-BRISK detection/description scheme, and by reporting processing speeds. Evaluations are conducted on the publicly available dataset of ICDAR2015 SmartDOC challenge 1. Finally, we prove that reducing the original keypoint set is always feasible and can be beneficial not only to processing speed but also to accuracy. |
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Address ![]() |
Kyoto; Japan; November 2017 | ||||
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; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RCR2017 | Serial | 3000 | ||
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Author | David Aldavert; Marçal Rusiñol; Ricardo Toledo | ||||
Title | Automatic Static/Variable Content Separation in Administrative Document Images | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | In this paper we present an automatic method for separating static and variable content from administrative document images. An alignment approach is able to unsupervisedly build probabilistic templates from a set of examples of the same document kind. Such templates define which is the likelihood of every pixel of being either static or variable content. In the extraction step, the same alignment technique is used to match
an incoming image with the template and to locate the positions where variable fields appear. We validate our approach on the public NIST Structured Tax Forms Dataset. |
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Address ![]() |
Kyoto; Japan; November 2017 | ||||
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; 600.121 | Approved | no | ||
Call Number | Admin @ si @ ART2017 | Serial | 3001 | ||
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Author | N. Nayef; F. Yin; I. Bizid; H .Choi; Y. Feng; Dimosthenis Karatzas; Z. Luo; Umapada Pal; Christophe Rigaud; J. Chazalon; W. Khlif; Muhammad Muzzamil Luqman; Jean-Christophe Burie; C.L. Liu; Jean-Marc Ogier | ||||
Title | ICDAR2017 Robust Reading Challenge on Multi-Lingual Scene Text Detection and Script Identification – RRC-MLT | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1454-1459 | ||
Keywords | |||||
Abstract | Text detection and recognition in a natural environment are key components of many applications, ranging from business card digitization to shop indexation in a street. This competition aims at assessing the ability of state-of-the-art methods to detect Multi-Lingual Text (MLT) in scene images, such as in contents gathered from the Internet media and in modern cities where multiple cultures live and communicate together. This competition is an extension of the Robust Reading Competition (RRC) which has been held since 2003 both in ICDAR and in an online context. The proposed competition is presented as a new challenge of the RRC. The dataset built for this challenge largely extends the previous RRC editions in many aspects: the multi-lingual text, the size of the dataset, the multi-oriented text, the wide variety of scenes. The dataset is comprised of 18,000 images which contain text belonging to 9 languages. The challenge is comprised of three tasks related to text detection and script classification. We have received a total of 16 participations from the research and industrial communities. This paper presents the dataset, the tasks and the findings of this RRC-MLT challenge. | ||||
Address ![]() |
Kyoto; Japan; November 2017 | ||||
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 | 978-1-5386-3586-5 | Medium | ||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.121 | Approved | no | ||
Call Number | Admin @ si @ NYB2017 | Serial | 3097 | ||
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Author | Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero | ||||
Title | e-Counterfeit: a mobile-server platform for document counterfeit detection | Type | Conference Article | ||
Year | 2017 | Publication | 14th IAPR International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that is usually printed in documents as IDs or banknotes. The main contribution of this work is the end-to-end mobile-server architecture, which provides a service for non-expert users and therefore can be used in several scenarios. The system also provides a crowdsourcing mode so labeled images can be gathered, generating databases for incremental training of the algorithms. | ||||
Address ![]() |
Kyoto; Japan; November 2017 | ||||
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; 600.061; 600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ BRL2018 | Serial | 3084 | ||
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Author | Alicia Fornes; Veronica Romero; Arnau Baro; Juan Ignacio Toledo; Joan Andreu Sanchez; Enrique Vidal; Josep Llados | ||||
Title | ICDAR2017 Competition on Information Extraction in Historical Handwritten Records | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1389-1394 | ||
Keywords | |||||
Abstract | The extraction of relevant information from historical handwritten document collections is one of the key steps in order to make these manuscripts available for access and searches. In this competition, the goal is to detect the named entities and assign each of them a semantic category, and therefore, to simulate the filling in of a knowledge database. This paper describes the dataset, the tasks, the evaluation metrics, the participants methods and the results. | ||||
Address ![]() |
Kyoto; Japan; November 2017 | ||||
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; 600.097; 601.225; 600.121 | Approved | no | ||
Call Number | Admin @ si @ FRB2017 | Serial | 3052 | ||
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Author | Dimosthenis Karatzas; Lluis Gomez; Marçal Rusiñol | ||||
Title | The Robust Reading Competition Annotation and Evaluation Platform | Type | Conference Article | ||
Year | 2017 | Publication | 1st International Workshop on Open Services and Tools for Document Analysis | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | The ICDAR Robust Reading Competition (RRC), initiated in 2003 and re-established in 2011, has become the defacto evaluation standard for the international community. Concurrent with its second incarnation in 2011, a continuous effort started to develop an online framework to facilitate the hosting and management of competitions. This short paper briefly outlines the Robust Reading Competition Annotation and Evaluation Platform, the backbone of the Robust Reading Competition, comprising a collection of tools and processes that aim to simplify the management and annotation
of data, and to provide online and offline performance evaluation and analysis services |
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Address ![]() |
Kyoto; Japan; November 2017 | ||||
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-OST | ||
Notes | DAG; 600.084; 600.121; 600.129 | Approved | no | ||
Call Number | Admin @ si @ KGR2017 | Serial | 3063 | ||
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Author | Raul Gomez; Baoguang Shi; Lluis Gomez; Lukas Numann; Andreas Veit; Jiri Matas; Serge Belongie; Dimosthenis Karatzas | ||||
Title | ICDAR2017 Robust Reading Challenge on COCO-Text | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | |||||
Address ![]() |
Kyoto; Japan; November 2017 | ||||
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; 600.121 | Approved | no | ||
Call Number | Admin @ si @ GSG2017 | Serial | 3076 | ||
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Author | Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds) | ||||
Title | Graphics Recognition: Achievements, Challenges, and Evolution | Type | Book Whole | ||
Year | 2010 | Publication | 8th International Workshop GREC 2009. | Abbreviated Journal | |
Volume | 6020 | Issue | Pages | ||
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Abstract | |||||
Address ![]() |
La Rochelle | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Link | Place of Publication | Editor | Jean-Marc Ogier; Wenyin Liu; Josep Llados | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Lecture Notes in Computer Science | Abbreviated Series Title | LNCS | |
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-3-642-13727-3 | Medium | ||
Area | Expedition | Conference | GREC | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ OLL2010 | Serial | 1976 | ||
Permanent link to this record |