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| Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
| Title | Noise suppression over bi-level graphical documents using a sparse representation | Type | Conference Article | ||
| Year | 2012 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
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| Address | Bordeaux | ||||
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| Area | Expedition | Conference | CIFED | ||
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DAG | Approved | no | ||
| Call Number | Admin @ si @ DTR2012b | Serial | 2136 | ||
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| Author | Jaume Gibert; Ernest Valveny; Horst Bunke; Alicia Fornes | ||||
| Title | On the Correlation of Graph Edit Distance and L1 Distance in the Attribute Statistics Embedding Space | Type | Conference Article | ||
| Year | 2012 | Publication | Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop | Abbreviated Journal | |
| Volume | 7626 | Issue | Pages | 135-143 | |
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| Abstract | Graph embeddings in vector spaces aim at assigning a pattern vector to every graph so that the problems of graph classification and clustering can be solved by using data processing algorithms originally developed for statistical feature vectors. An important requirement graph features should fulfil is that they reproduce as much as possible the properties among objects in the graph domain. In particular, it is usually desired that distances between pairs of graphs in the graph domain closely resemble those between their corresponding vectorial representations. In this work, we analyse relations between the edit distance in the graph domain and the L1 distance of the attribute statistics based embedding, for which good classification performance has been reported on various datasets. We show that there is actually a high correlation between the two kinds of distances provided that the corresponding parameter values that account for balancing the weight between node and edge based features are properly selected. | ||||
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| Publisher | Springer-Berlag, Berlin | Place of Publication | Editor | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-34165-6 | Medium | ||
| Area | Expedition | Conference | SSPR&SPR | ||
| Notes |
DAG | Approved | no | ||
| Call Number | Admin @ si @ GVB2012c | Serial | 2167 | ||
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| Author | David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha | ||||
| Title | On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts | Type | Conference Article | ||
| Year | 2012 | Publication | 13th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 763-768 | ||
| Keywords | document image processing;handwritten character recognition;history;image segmentation;Spanish document;historical document;line segmentation;old handwritten document;old manuscript;word segmentation;Bifurcation;Dynamic programming;Handwriting recognition;Image segmentation;Measurement;Noise;Skeleton;Segmentation;document analysis;document and text processing;handwriting analysis;heuristics;path-finding | ||||
| Abstract | he objective of this work is to show the importance of a good line segmentation to obtain better results in the segmentation of words of historical documents. We have used the approach developed by Manmatha and Rothfeder [1] to segment words in old handwritten documents. In their work the lines of the documents are extracted using projections. In this work, we have developed an approach to segment lines more efficiently. The new line segmentation algorithm tackles with skewed, touching and noisy lines, so it is significantly improves word segmentation. Experiments using Spanish documents from the Marriages Database of the Barcelona Cathedral show that this approach reduces the error rate by more than 20% | ||||
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| ISSN | ISBN | 978-1-4673-2262-1 | Medium | ||
| Area | Expedition | Conference | ICFHR | ||
| Notes |
DAG | Approved | no | ||
| Call Number | Admin @ si @ FLF2012 | Serial | 2200 | ||
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| Author | Jaume Gibert | ||||
| Title | Vector Space Embedding of Graphs via Statistics of Labelling Information | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Pattern recognition is the task that aims at distinguishing objects among different classes. When such a task wants to be solved in an automatic way a crucial step is how to formally represent such patterns to the computer. Based on the different representational formalisms, we may distinguish between statistical and structural pattern recognition. The former describes objects as a set of measurements arranged in the form of what is called a feature vector. The latter assumes that relations between parts of the underlying objects need to be explicitly represented and thus it uses relational structures such as graphs for encoding their inherent information. Vector spaces are a very flexible mathematical structure that has allowed to come up with several efficient ways for the analysis of patterns under the form of feature vectors. Nevertheless, such a representation cannot explicitly cope with binary relations between parts of the objects and it is restricted to measure the exact same number of features for each pattern under study regardless of their complexity. Graph-based representations present the contrary situation. They can easily adapt to the inherent complexity of the patterns but introduce a problem of high computational complexity, hindering the design of efficient tools to process and analyse patterns.
Solving this paradox is the main goal of this thesis. The ideal situation for solving pattern recognition problems would be to represent the patterns using relational structures such as graphs, and to be able to use the wealthy repository of data processing tools from the statistical pattern recognition domain. An elegant solution to this problem is to transform the graph domain into a vector domain where any processing algorithm can be applied. In other words, by mapping each graph to a point in a vector space we automatically get access to the rich set of algorithms from the statistical domain to be applied in the graph domain. Such methodology is called graph embedding. In this thesis we propose to associate feature vectors to graphs in a simple and very efficient way by just putting attention on the labelling information that graphs store. In particular, we count frequencies of node labels and of edges between labels. Although their locality, these features are able to robustly represent structurally global properties of graphs, when considered together in the form of a vector. We initially deal with the case of discrete attributed graphs, where features are easy to compute. The continuous case is tackled as a natural generalization of the discrete one, where rather than counting node and edge labelling instances, we count statistics of some representatives of them. We encounter how the proposed vectorial representations of graphs suffer from high dimensionality and correlation among components and we face these problems by feature selection algorithms. We also explore how the diversity of different embedding representations can be exploited in order to boost the performance of base classifiers in a multiple classifier systems framework. An extensive experimental evaluation finally shows how the methodology we propose can be efficiently computed and compete with other graph matching and embedding methodologies. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Ernest Valveny | |
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| Notes |
DAG | Approved | no | ||
| Call Number | Admin @ si @ Gib2012 | Serial | 2204 | ||
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| Author | Nuria Cirera | ||||
| Title | Recognition of Handwritten Historical Documents | Type | Report | ||
| Year | 2012 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 174 | Issue | Pages | ||
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| Corporate Author | Thesis | Master's thesis | |||
| Publisher | Place of Publication | Editor | |||
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| Notes |
DAG | Approved | no | ||
| Call Number | Admin @ si @ Cir2012 | Serial | 2416 | ||
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| Author | Ernest Valveny; Robert Benavente; Agata Lapedriza; Miquel Ferrer; Jaume Garcia; Gemma Sanchez | ||||
| Title | Adaptation of a computer programming course to the EXHE requirements: evaluation five years later | Type | Miscellaneous | ||
| Year | 2012 | Publication | European Journal of Engineering Education | Abbreviated Journal | |
| Volume | 37 | Issue | 3 | Pages | 243-254 |
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| Notes |
DAG; CIC; OR; invisible;MV | Approved | no | ||
| Call Number | Admin @ si @ VBL2012 | Serial | 2070 | ||
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| Author | Albert Clapes; Miguel Reyes; Sergio Escalera | ||||
| Title | User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis | Type | Conference Article | ||
| Year | 2012 | Publication | 7th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
| Volume | 7378 | Issue | Pages | 1-11 | |
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| Abstract | We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. | ||||
| Address | Mallorca | ||||
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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 | 978-3-642-31566-4 | Medium | |
| Area | Expedition | Conference | AMDO | ||
| Notes |
HUPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ CRE2012 | Serial | 2010 | ||
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| Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
| Title | Three-Dimensional Design of Error Correcting Output Codes | Type | Conference Article | ||
| Year | 2012 | Publication | 8th International Conference on Machine Learning and Data Mining | Abbreviated Journal | |
| Volume | Issue | Pages | 29- | ||
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| Address | Berlin, Germany | ||||
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| Area | Expedition | Conference | MLDM | ||
| Notes |
HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGE2012a | Serial | 2041 | ||
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| Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
| Title | Error Correcting Output Codes for multiclass classification: Application to two image vision problems | Type | Conference Article | ||
| Year | 2012 | Publication | 16th symposium on Artificial Intelligence & Signal Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 508-513 | ||
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| Abstract | Error-correcting output codes (ECOC) represents a powerful framework to deal with multiclass classification problems based on combining binary classifiers. The key factor affecting the performance of ECOC methods is the independence of binary classifiers, without which the ECOC method would be ineffective. In spite of its ability on classification of problems with relatively large number of classes, it has been applied in few real world problems. In this paper, we investigate the behavior of the ECOC approach on two image vision problems: logo recognition and shape classification using Decision Tree and AdaBoost as the base learners. The results show that the ECOC method can be used to improve the classification performance in comparison with the classical multiclass approaches. | ||||
| Address | Shiraz, Iran | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE Xplore | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4673-1478-7 | Medium | ||
| Area | Expedition | Conference | AISP | ||
| Notes |
HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGE2012b | Serial | 2042 | ||
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| Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
| Title | Efficient pairwise classification using Local Cross Off strategy | Type | Conference Article | ||
| Year | 2012 | Publication | 25th Canadian Conference on Artificial Intelligence | Abbreviated Journal | |
| Volume | 7310 | Issue | Pages | 25-36 | |
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| Abstract | The pairwise classification approach tends to perform better than other well-known approaches when dealing with multiclass classification problems. In the pairwise approach, however, the nuisance votes of many irrelevant classifiers may result in a wrong prediction class. To overcome this problem, a novel method, Local Crossing Off (LCO), is presented and evaluated in this paper. The proposed LCO system takes advantage of nearest neighbor classification algorithm because of its simplicity and speed, as well as the strength of other two powerful binary classifiers to discriminate between two classes. This paper provides a set of experimental results on 20 datasets using two base learners: Neural Networks and Support Vector Machines. The results show that the proposed technique not only achieves better classification accuracy, but also is computationally more efficient for tackling classification problems which have a relatively large number of target classes. | ||||
| Address | Toronto, Ontario | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-30352-4 | Medium | |
| Area | Expedition | Conference | AI | ||
| Notes |
HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGE2012c | Serial | 2044 | ||
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| Author | Miguel Reyes; Albert Clapes; Luis Felipe Mejia; Jose Ramirez; Juan R Revilla; Sergio Escalera | ||||
| Title | Posture Analysis and Range of Movement Estimation using Depth Maps | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis | Abbreviated Journal | |
| Volume | 7854 | Issue | Pages | 97-105 | |
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| Abstract | World Health Organization estimates that 80% of the world population is affected of back pain during his life. Current practices to analyze back problems are expensive, subjective, and invasive. In this work, we propose a novel tool for posture and range of movement estimation based on the analysis of 3D information from depth maps. Given a set of keypoints defined by the user, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matching using a novel point-to-point fitting procedure, and accurate measurements about posture, spinal curvature, and range of movement are computed. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent musculoskeletal disorders, such as back pain, as well as tracking the posture evolution of patients in rehabilitation treatments. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-40302-6 | Medium | |
| Area | Expedition | Conference | WDIA | ||
| Notes |
HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ RCM2012 | Serial | 2121 | ||
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| Author | Antonio Hernandez; Miguel Reyes; Victor Ponce; Sergio Escalera | ||||
| Title | GrabCut-Based Human Segmentation in Video Sequences | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 11 | Pages | 15376-15393 |
| Keywords | segmentation; human pose recovery; GrabCut; GraphCut; Active Appearance Models; Conditional Random Field | ||||
| Abstract | In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology. | ||||
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| Area | Expedition | Conference | |||
| Notes |
HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ HRP2012 | Serial | 2147 | ||
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| Author | Antonio Hernandez; Miguel Angel Bautista; Xavier Perez Sala; Victor Ponce; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera | ||||
| Title | BoVDW: Bag-of-Visual-and-Depth-Words for Gesture Recognition | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
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| Abstract | We present a Bag-of-Visual-and-Depth-Words (BoVDW) model for gesture recognition, an extension of the Bag-of-Visual-Words (BoVW) model, that benefits from the multimodal fusion of visual and depth features. State-of-the-art RGB and depth features, including a new proposed depth descriptor, are analysed and combined in a late fusion fashion. The method is integrated in a continuous gesture recognition pipeline, where Dynamic Time Warping (DTW) algorithm is used to perform prior segmentation of gestures. Results of the method in public data sets, within our gesture recognition pipeline, show better performance in comparison to a standard BoVW model. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes |
HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ HBP2012 | Serial | 2122 | ||
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| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title | Assessing agonist efficacy in an uncertain Em world | Type | Conference Article | ||
| Year | 2012 | Publication | 40th Keystone Symposia on mollecular and celular biology | Abbreviated Journal | |
| Volume | Issue | Pages | 79 | ||
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| Abstract | The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed. |
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| Address | Fairmont Banff Springs, Banff, Alberta, Canada | ||||
| Corporate Author | Keystone Symposia | Thesis | |||
| Publisher | Keystone Symposia | Place of Publication | Editor | A. Christopoulus and M. Bouvier | |
| Language | english | Summary Language | english | Original Title | |
| Series Editor | Keystone Symposia | Series Title | Abbreviated Series Title | ||
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| Area | Expedition | Conference | KSMCB | ||
| Notes |
IAM | Approved | no | ||
| Call Number | IAM @ iam @ RGG2012 | Serial | 1855 | ||
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| Author | Alberto Hidalgo; Ferran Poveda; Enric Marti;Debora Gil;Albert Andaluz; Francesc Carreras; Manuel Ballester | ||||
| Title | Evidence of continuous helical structure of the cardiac ventricular anatomy assessed by diffusion tensor imaging magnetic resonance multiresolution tractography | Type | Journal Article | ||
| Year | 2012 | Publication | European Radiology | Abbreviated Journal | ECR |
| Volume | 3 | Issue | 1 | Pages | 361-362 |
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| Abstract | Deep understanding of myocardial structure linking morphology and func- tion of the heart would unravel crucial knowledge for medical and surgical clinical procedures and studies. Diffusion tensor MRI provides a discrete measurement of the 3D arrangement of myocardial fibres by the observation of local anisotropic
diffusion of water molecules in biological tissues. In this work, we present a multi- scale visualisation technique based on DT-MRI streamlining capable of uncovering additional properties of the architectural organisation of the heart. Methods and Materials: We selected the John Hopkins University (JHU) Canine Heart Dataset, where the long axis cardiac plane is aligned with the scanner’s Z- axis. Their equipment included a 4-element passed array coil emitting a 1.5 T. For DTI acquisition, a 3D-FSE sequence is apply. We used 200 seeds for full-scale tractography, while we applied a MIP mapping technique for simplified tractographic reconstruction. In this case, we reduced each DTI 3D volume dimensions by order- two magnitude before streamlining. Our simplified tractographic reconstruction method keeps the main geometric features of fibres, allowing for an easier identification of their global morphological disposition, including the ventricular basal ring. Moreover, we noticed a clearly visible helical disposition of the myocardial fibres, in line with the helical myocardial band ventricular structure described by Torrent-Guasp. Finally, our simplified visualisation with single tracts identifies the main segments of the helical ventricular architecture. DT-MRI makes possible the identification of a continuous helical architecture of the myocardial fibres, which validates Torrent-Guasp’s helical myocardial band ventricular anatomical model. |
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| Address | Viena, Austria | ||||
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| Publisher | Springer Link | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1869-4101 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes |
IAM | Approved | no | ||
| Call Number | IAM @ iam @ HPM2012 | Serial | 1858 | ||
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