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| Author | Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez | ||||
| Title | Multi-task Bilinear Classifiers for Visual Domain Adaptation | Type  |
Conference Article | ||
| Year | 2013 | Publication | Advances in Neural Information Processing Systems Workshop | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Domain Adaptation; Pedestrian Detection; ADAS | ||||
| Abstract | We propose a method that aims to lessen the significant accuracy degradation
that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation. The bilinear classifier encodes the feature transformation and classification parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines. |
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| Address | Lake Tahoe; Nevada; USA; December 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 | NIPSW | ||
| Notes | ADAS; 600.054; 600.057; 601.217;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ XRH2013 | Serial | 2340 | ||
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| Author | David Geronimo; Frederic Lerasle; Antonio Lopez | ||||
| Title | State-driven particle filter for multi-person tracking | Type |
Conference Article | ||
| Year | 2012 | Publication | 11th International Conference on Advanced Concepts for Intelligent Vision Systems | Abbreviated Journal | |
| Volume | 7517 | Issue | Pages | 467-478 | |
| Keywords | human tracking | ||||
| Abstract | Multi-person tracking can be exploited in applications such as driver assistance, surveillance, multimedia and human-robot interaction. With the help of human detectors, particle filters offer a robust method able to filter noisy detections and provide temporal coherence. However, some traditional problems such as occlusions with other targets or the scene, temporal drifting or even the lost targets detection are rarely considered, making the systems performance decrease. Some authors propose to overcome these problems using heuristics not explained
and formalized in the papers, for instance by defining exceptions to the model updating depending on tracks overlapping. In this paper we propose to formalize these events by the use of a state-graph, defining the current state of the track (e.g., potential , tracked, occluded or lost) and the transitions between states in an explicit way. This approach has the advantage of linking track actions such as the online underlying models updating, which gives flexibility to the system. It provides an explicit representation to adapt the multiple parallel trackers depending on the context, i.e., each track can make use of a specific filtering strategy, dynamic model, number of particles, etc. depending on its state. We implement this technique in a single-camera multi-person tracker and test it in public video sequences. |
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| Address | Brno, Chzech Republic | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer | Place of Publication | Heidelberg | Editor | J. Blanc-Talon et al. |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ACIVS | ||
| Notes | ADAS | Approved | yes | ||
| Call Number | GLL2012; ADAS @ adas @ gll2012a | Serial | 1990 | ||
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| Author | Sergio Escalera; Josep Moya; Laura Igual; Veronica Violant; Maria Teresa Anguera | ||||
| Title | Automatic Human Behavior Analysis in ADHD | Type |
Conference Article | ||
| Year | 2012 | Publication | Eunethydis 2nd International ADHD Conference | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | |||||
| Abstract | Poster | ||||
| 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 | EUNETHYDIS | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ EMI2012a | Serial | 2058 | ||
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| Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
| Title | New Approach for Symbol Recognition Combining Shape Context of Interest Points with Sparse Representation | Type |
Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 265-269 | ||
| Keywords | |||||
| Abstract | In this paper, we propose a new approach for symbol description. Our method is built based on the combination of shape context of interest points descriptor and sparse representation. More specifically, we first learn a dictionary describing shape context of interest point descriptors. Then, based on information retrieval techniques, we build a vector model for each symbol based on its sparse representation in a visual vocabulary whose visual words are columns in the learneddictionary. The retrieval task is performed by ranking symbols based on similarity between vector models. Evaluation of our method, using benchmark datasets, demonstrates the validity of our approach and shows that it outperforms related state-of-theart methods. | ||||
| Address | Washington; USA; August 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 | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ DTR2013b | Serial | 2331 | ||
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| Author | R. Bertrand; P. Gomez-Krämer; Oriol Ramos Terrades; P. Franco; Jean-Marc Ogier | ||||
| Title | A System Based On Intrinsic Features for Fraudulent Document Detection | Type |
Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 106-110 | ||
| Keywords | paper document; document analysis; fraudulent document; forgery; fake | ||||
| Abstract | Paper documents still represent a large amount of information supports used nowadays and may contain critical data. Even though official documents are secured with techniques such as printed patterns or artwork, paper documents suffer froma lack of security.
However, the high availability of cheap scanning and printing hardware allows non-experts to easily create fake documents. As the use of a watermarking system added during the document production step is hardly possible, solutions have to be proposed to distinguish a genuine document from a forged one. In this paper, we present an automatic forgery detection method based on document’s intrinsic features at character level. This method is based on the one hand on outlier character detection in a discriminant feature space and on the other hand on the detection of strictly similar characters. Therefore, a feature set iscomputed for all characters. Then, based on a distance between characters of the same class. |
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| Address | Washington; USA; August 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 | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ BGR2013a | Serial | 2332 | ||
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| Author | Javier Marin; David Vazquez; Antonio Lopez; Jaume Amores; Bastian Leibe | ||||
| Title | Random Forests of Local Experts for Pedestrian Detection | Type |
Conference Article | ||
| Year | 2013 | Publication | 15th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 2592 - 2599 | ||
| Keywords | ADAS; Random Forest; Pedestrian Detection | ||||
| Abstract | Pedestrian detection is one of the most challenging tasks in computer vision, and has received a lot of attention in the last years. Recently, some authors have shown the advantages of using combinations of part/patch-based detectors in order to cope with the large variability of poses and the existence of partial occlusions. In this paper, we propose a pedestrian detection method that efficiently combines multiple local experts by means of a Random Forest ensemble. The proposed method works with rich block-based representations such as HOG and LBP, in such a way that the same features are reused by the multiple local experts, so that no extra computational cost is needed with respect to a holistic method. Furthermore, we demonstrate how to integrate the proposed approach with a cascaded architecture in order to achieve not only high accuracy but also an acceptable efficiency. In particular, the resulting detector operates at five frames per second using a laptop machine. We tested the proposed method with well-known challenging datasets such as Caltech, ETH, Daimler, and INRIA. The method proposed in this work consistently ranks among the top performers in all the datasets, being either the best method or having a small difference with the best one. | ||||
| Address | Sydney; Australia; December 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1550-5499 | ISBN | Medium | ||
| Area | Expedition | Conference | ICCV | ||
| Notes | ADAS; 600.057; 600.054 | Approved | no | ||
| Call Number | ADAS @ adas @ MVL2013 | Serial | 2333 | ||
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| Author | Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny | ||||
| Title | Handwritten Word Spotting with Corrected Attributes | Type |
Conference Article | ||
| Year | 2013 | Publication | 15th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 1017-1024 | ||
| Keywords | |||||
| Abstract | We propose an approach to multi-writer word spotting, where the goal is to find a query word in a dataset comprised of document images. We propose an attributes-based approach that leads to a low-dimensional, fixed-length representation of the word images that is fast to compute and, especially, fast to compare. This approach naturally leads to an unified representation of word images and strings, which seamlessly allows one to indistinctly perform query-by-example, where the query is an image, and query-by-string, where the query is a string. We also propose a calibration scheme to correct the attributes scores based on Canonical Correlation Analysis that greatly improves the results on a challenging dataset. We test our approach on two public datasets showing state-of-the-art results. | ||||
| Address | Sydney; Australia; December 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 | 1550-5499 | ISBN | Medium | ||
| Area | Expedition | Conference | ICCV | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ AGF2013 | Serial | 2327 | ||
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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 | |
| Keywords | |||||
| 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 | ||
| Permanent link to this record | |||||
| 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 | ||
| Keywords | |||||
| 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 | ||||
| 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 | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ CrT2013 | Serial | 2329 | ||
| Permanent link to this record | |||||
| 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 | ||
| Keywords | |||||
| 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 | ||||
| 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 | 978-1-4503-1789-4 | Medium | ||
| Area | Expedition | Conference | ACM-DocEng | ||
| Notes | DAG; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ DTR2013a | Serial | 2330 | ||
| Permanent link to this record | |||||
| 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 | ||
| Keywords | |||||
| 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 | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| 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 | 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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| Abstract | |||||
| Address | Vic; October 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 | 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 | ||||
| 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 | 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 | ||
| Permanent link to this record | |||||
| 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 | ||||
| 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; 600.045; 600.056; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ HFF2013a | Serial | 2320 | ||
| Permanent link to this record | |||||
| 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 | ||||
| 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; 600.045 | Approved | no | ||
| Call Number | Admin @ si @ HVS2013a | Serial | 2321 | ||
| Permanent link to this record | |||||