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| Author | Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Bemedi | ||||
| Title | Page Segmentation of Structured Documents Using 2D Stochastic Context-Free Grammars | Type | Conference Article | ||
| Year | 2013 | Publication | 6th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 7887 | Issue | Pages | 133-140 | |
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| Abstract | In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for page segmentation of structured documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the page segmentation is obtained as the most likely hypothesis according to a grammar. This approach is compared to Conditional Random Fields and results show significant improvements in several cases. Furthermore, grammars provide a detailed segmentation that allowed a semantic evaluation which also validates this model. | ||||
| Address | Madeira; Portugal; June 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 | 978-3-642-38627-5 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | DAG; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ ACS2013 | Serial | 2328 | ||
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| Author | Francisco Cruz; Oriol Ramos Terrades | ||||
| Title | Handwritten Line Detection via an EM Algorithm | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 718-722 | ||
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| Abstract | In this paper we present a handwritten line segmentation method devised to work on documents composed of several paragraphs with multiple line orientations. The method is based on a variation of the EM algorithm for the estimation of a set of regression lines between the connected components that compose the image. We evaluated our method on the ICDAR2009 handwriting segmentation contest dataset with promising results that overcome most of the presented methods. In addition, we prove the usability of the presented method by performing line segmentation on the George Washington database obtaining encouraging results. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ CrT2013 | Serial | 2329 | ||
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| Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
| Title | Document noise removal using sparse representations over learned dictionary | Type | Conference Article | ||
| Year | 2013 | Publication | Symposium on Document engineering | Abbreviated Journal | |
| Volume | Issue | Pages | 161-168 | ||
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| Abstract | best paper award
In this paper, we propose an algorithm for denoising document images using sparse representations. Following a training set, this algorithm is able to learn the main document characteristics and also, the kind of noise included into the documents. In this perspective, we propose to model the noise energy based on the normalized cross-correlation between pairs of noisy and non-noisy documents. Experimental results on several datasets demonstrate the robustness of our method compared with the state-of-the-art. |
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| Address | Barcelona; October 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | 978-1-4503-1789-4 | Medium | ||
| Area | Expedition | Conference | ACM-DocEng | ||
| Notes | DAG; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ DTR2013a | Serial | 2330 | ||
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| Author | Jon Almazan; Alicia Fornes; Ernest Valveny | ||||
| Title | A Deformable HOG-based Shape Descriptor | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1022-1026 | ||
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| Abstract | In this paper we deal with the problem of recognizing handwritten shapes. We present a new deformable feature extraction method that adapts to the shape to be described, dealing in this way with the variability introduced in the handwriting domain. It consists in a selection of the regions that best define the shape to be described, followed by the computation of histograms of oriented gradients-based features over these points. Our results significantly outperform other descriptors in the literature for the task of hand-drawn shape recognition and handwritten word retrieval | ||||
| Address | Washington; USA; August 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ AFV2013 | Serial | 2326 | ||
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| Author | David Geronimo; Antonio Lopez | ||||
| Title | Vision-based Pedestrian Protection Systems for Intelligent Vehicles | Type | Book Whole | ||
| Year | 2014 | Publication | SpringerBriefs in Computer Science | Abbreviated Journal | |
| Volume | Issue | Pages | 1-114 | ||
| Keywords | Computer Vision; Driver Assistance Systems; Intelligent Vehicles; Pedestrian Detection; Vulnerable Road Users | ||||
| Abstract | Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented. | ||||
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| Publisher | Springer Briefs in Computer Vision | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4614-7986-4 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | GeL2014 | Serial | 2325 | ||
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| Author | Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny | ||||
| Title | Notation-invariant patch-based wall detector in architectural floor plans | Type | Book Chapter | ||
| Year | 2013 | Publication | Graphics Recognition. New Trends and Challenges | Abbreviated Journal | |
| Volume | 7423 | Issue | Pages | 79--88 | |
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| Abstract | Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper. | ||||
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| 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 | 978-3-642-36823-3 | Medium | |
| Area | Expedition | Conference | |||
| Notes | DAG; 600.045; 600.056; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ HMS2013 | Serial | 2322 | ||
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| Author | Alvaro Cepero; Albert Clapes; Sergio Escalera | ||||
| Title | Quantitative analysis of non-verbal communication for competence analysis | Type | Conference Article | ||
| Year | 2013 | Publication | 16th Catalan Conference on Artificial Intelligence | Abbreviated Journal | |
| Volume | 256 | Issue | Pages | 105-114 | |
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| Address | Vic; October 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference | CCIA | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ CCE2013 | Serial | 2324 | ||
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| Author | Lluis Pere de las Heras; David Fernandez; Ernest Valveny; Josep Llados; Gemma Sanchez | ||||
| Title | Unsupervised wall detector in architectural floor plan | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1245-1249 | ||
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| Abstract | Wall detection in floor plans is a crucial step in a complete floor plan recognition system. Walls define the main structure of buildings and convey essential information for the detection of other structural elements. Nevertheless, wall segmentation is a difficult task, mainly because of the lack of a standard graphical notation. The existing approaches are restricted to small group of similar notations or require the existence of pre-annotated corpus of input images to learn each new notation. In this paper we present an automatic wall segmentation system, with the ability to handle completely different notations without the need of any annotated dataset. It only takes advantage of the general knowledge that walls are a repetitive element, naturally distributed within the plan and commonly modeled by straight parallel lines. The method has been tested on four datasets of real floor plans with different notations, and compared with the state-of-the-art. The results show its suitability for different graphical notations, achieving higher recall rates than the rest of the methods while keeping a high average precision. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.061; 600.056; 600.045 | Approved | no | ||
| Call Number | Admin @ si @ HFV2013 | Serial | 2319 | ||
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| Author | Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez;Josep Llados | ||||
| Title | Perceptual retrieval of architectural floor plans | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | This paper proposes a runlength histogram signature as a percetual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query,
similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Preliminary results show the interest of the proposed approach and opens a challenging research line in graphics recognition. |
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| Address | Bethlehem; PA; USA; August 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | GREC | ||
| Notes | DAG; 600.045; 600.056; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ HFF2013a | Serial | 2320 | ||
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| Author | Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez | ||||
| Title | Combining structural and statistical strategies for unsupervised wall detection in floor plans | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | This paper presents an evolution of the first unsupervised wall segmentation method in floor plans, that was presented by the authors in [1]. This first approach, contrarily to the existing ones, is able to segment walls independently to their notation and without the need of any pre-annotated data
to learn their visual appearance. Despite the good performance of the first approach, some specific cases, such as curved shaped walls, were not correctly segmented since they do not agree the strict structural assumptions that guide the whole methodology in order to be able to learn, in an unsupervised way, the structure of a wall. In this paper, we refine this strategy by dividing the process in two steps. In a first step, potential wall segments are extracted unsupervisedly using a modification of [1], by restricting even more the areas considered as walls in a first moment. In a second step, these segments are used to learn and spot lost instances based on a modified version of [2], also presented by the authors. The presented combined method have been tested on 4 datasets with different notations and compared with the stateof-the-art applyed on the same datasets. The results show its adaptability to different wall notations and shapes, significantly outperforming the original approach. |
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| Address | Bethlehem; PA; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference | GREC | ||
| Notes | DAG; 600.045 | Approved | no | ||
| Call Number | Admin @ si @ HVS2013a | Serial | 2321 | ||
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| Author | Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu | ||||
| Title | New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired | Type | Journal Article | ||
| Year | 2014 | Publication | Computer | Abbreviated Journal | COMP |
| Volume | 47 | Issue | 4 | Pages | 52-58 |
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| Abstract | Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0018-9162 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ TSR2014a | Serial | 2317 | ||
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| Author | Dimosthenis Karatzas; Faisal Shafait; Seiichi Uchida; Masakazu Iwamura; Lluis Gomez; Sergi Robles; Joan Mas; David Fernandez; Jon Almazan; Lluis Pere de las Heras | ||||
| Title | ICDAR 2013 Robust Reading Competition | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1484-1493 | ||
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| Abstract | This report presents the final results of the ICDAR 2013 Robust Reading Competition. The competition is structured in three Challenges addressing text extraction in different application domains, namely born-digital images, real scene images and real-scene videos. The Challenges are organised around specific tasks covering text localisation, text segmentation and word recognition. The competition took place in the first quarter of 2013, and received a total of 42 submissions over the different tasks offered. This report describes the datasets and ground truth specification, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.056 | Approved | no | ||
| Call Number | Admin @ si @ KSU2013 | Serial | 2318 | ||
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| Author | Lluis Gomez | ||||
| Title | Perceptual Organization for Text Extraction in Natural Scenes | Type | Report | ||
| Year | 2012 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 173 | Issue | Pages | ||
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| Address | Bellaterra | ||||
| Corporate Author | Thesis | Master's thesis | |||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ Gom2012 | Serial | 2309 | ||
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| Author | Lluis Gomez; Dimosthenis Karatzas | ||||
| Title | Multi-script Text Extraction from Natural Scenes | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 467-471 | ||
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| Abstract | Scene text extraction methodologies are usually based in classification of individual regions or patches, using a priori knowledge for a given script or language. Human perception of text, on the other hand, is based on perceptual organisation through which text emerges as a perceptually significant group of atomic objects. Therefore humans are able to detect text even in languages and scripts never seen before. In this paper, we argue that the text extraction problem could be posed as the detection of meaningful groups of regions. We present a method built around a perceptual organisation framework that exploits collaboration of proximity and similarity laws to create text-group hypotheses. Experiments demonstrate that our algorithm is competitive with state of the art approaches on a standard dataset covering text in variable orientations and two languages. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.056; 601.158; 601.197 | Approved | no | ||
| Call Number | Admin @ si @ GoK2013 | Serial | 2310 | ||
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| Author | Adriana Romero; Carlo Gatta | ||||
| Title | Do We Really Need All These Neurons? | Type | Conference Article | ||
| Year | 2013 | Publication | 6th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 7887 | Issue | Pages | 460--467 | |
| Keywords | Retricted Boltzmann Machine; hidden units; unsupervised learning; classification | ||||
| Abstract | Restricted Boltzmann Machines (RBMs) are generative neural networks that have received much attention recently. In particular, choosing the appropriate number of hidden units is important as it might hinder their representative power. According to the literature, RBM require numerous hidden units to approximate any distribution properly. In this paper, we present an experiment to determine whether such amount of hidden units is required in a classification context. We then propose an incremental algorithm that trains RBM reusing the previously trained parameters using a trade-off measure to determine the appropriate number of hidden units. Results on the MNIST and OCR letters databases show that using a number of hidden units, which is one order of magnitude smaller than the literature estimate, suffices to achieve similar performance. Moreover, the proposed algorithm allows to estimate the required number of hidden units without the need of training many RBM from scratch. | ||||
| Address | Madeira; Portugal; June 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 | 978-3-642-38627-5 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | MILAB; 600.046 | Approved | no | ||
| Call Number | Admin @ si @ RoG2013 | Serial | 2311 | ||
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