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Enric Marti; Carme Julia; Debora Gil |
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Una experiencia de PBL en la docencia de la asignatura de Graficos por Computador en Ingenieria Informatica |
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Miscellaneous |
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2006 |
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IV Congreso Internacional Docencia Universitaria e Innovacion (CIDUI´06) |
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Barcelona |
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IAM;ADAS; |
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IAM @ iam @ MJG2006b |
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1123 |
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Author |
Enric Marti; J. Rocarias; A. Sanchez; Petia Radeva; Ricardo Toledo; Jordi Vitria |
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Title |
Caronte: un gestor documental para asignaturas del EEES |
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2006 |
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III Jornades de Innovacio Docent |
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UAB, Bellaterra |
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IAM;RV;OR;MILAB;ADAS;MV |
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BCNPCL @ bcnpcl @ MRS2006b |
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1124 |
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Author |
Enric Marti; J. Rocarias; Petia Radeva; H. Tizon; Jordi Vitria |
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Title |
Caronte. Un gestor documental para asignaturas de universidad en el EEES |
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Miscellaneous |
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2007 |
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Desarrollo de gestion de grupos, encuestas y autoevaluacion, MoodleMoot 2007 |
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IAM;OR;MILAB;MV |
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BCNPCL @ bcnpcl @ MRR2007b |
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1128 |
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Author |
Francesco Ciompi |
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Title |
ECOC-based Plaque Classification using In-vivo and Exvivo Intravascular Ultrasound Data |
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Miscellaneous |
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2008 |
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CVC Technical Report #125 |
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Bellaterra (Spain) |
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no |
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Admin @ si @ Cio2008 |
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1145 |
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Author |
Carles Fernandez; Jordi Gonzalez |
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Title |
A Multilingually-Extensible Module for Natural Language Generation |
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2008 |
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CVC Technical Report #120 |
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Barcelona, Spain |
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ISE @ ise @ FeG2008 |
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1146 |
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Author |
Ognjen Rudovic; Jordi Gonzalez |
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Title |
Building Temporal Templates for Human Behaviour Classification |
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2008 |
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CVC Technical Report #127 |
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Barcelona, Spain |
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ISE @ ise @ RuG 2008 |
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1147 |
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Author |
Marco Pedersoli |
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Title |
A Multiresolution Cascade for Human Detection |
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Miscellaneous |
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2008 |
Publication |
CVC Technical Report #126 |
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Barcelona, Spain |
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ISE |
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Admin @ si @ Ped2008 |
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1148 |
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Author |
Bhaskar Chakraborty |
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Title |
View-Invariant Human-Body Detection with Extension to Human Action Recognition using Component Wise HMM of Body Parts |
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Miscellaneous |
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2008 |
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CVC Technical Report #123 |
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Barcelona, Spain |
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ISE |
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no |
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Admin @ si @ Cha2008 |
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1149 |
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Author |
Mohammad Rouhani |
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Title |
3D Data Fitting and Tracking for Real Time Applications |
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Report |
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2009 |
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CVC Technical Report |
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138 |
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138 |
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Barcelona, Spain |
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Master's thesis |
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invisible;ADAS |
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no |
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Admin @ si @ Rou2009 |
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1150 |
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Author |
Pierluigi Casale |
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Title |
Social Environment Description from Data Collected with a Wearable Device |
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Miscellaneous |
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2008 |
Publication |
CVC Technical Report #124 |
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Barcelona, Spain |
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no |
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Admin @ si @ Cas2008 |
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1151 |
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Author |
Nicola Bellotto; Eric Sommerlade; Ben Benfold; Charles Bibby; I. Reid; Daniel Roth; Luc Van Gool; Carles Fernandez; Jordi Gonzalez |
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Title |
A Distributed Camera System for Multi-Resolution Surveillance |
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Conference Article |
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2009 |
Publication |
3rd ACM/IEEE International Conference on Distributed Smart Cameras |
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10.1109/ICDSC.2009.5289413 |
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We describe an architecture for a multi-camera, multi-resolution surveillance system. The aim is to support a set of distributed static and pan-tilt-zoom (PTZ) cameras and visual tracking algorithms, together with a central supervisor unit. Each camera (and possibly pan-tilt device) has a dedicated process and processor. Asynchronous interprocess communications and archiving of data are achieved in a simple and effective way via a central repository, implemented using an SQL database. Visual tracking data from static views are stored dynamically into tables in the database via client calls to the SQL server. A supervisor process running on the SQL server determines if active zoom cameras should be dispatched to observe a particular target, and this message is effected via writing demands into another database table. We show results from a real implementation of the system comprising one static camera overviewing the environment under consideration and a PTZ camera operating under closed-loop velocity control, which uses a fast and robust level-set-based region tracker. Experiments demonstrate the effectiveness of our approach and its feasibility to multi-camera systems for intelligent surveillance. |
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Como, Italy |
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ICDSC |
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Approved |
no |
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Call Number |
ISE @ ise @ BSB2009 |
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1205 |
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Author |
Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez |
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Title |
Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences |
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2010 |
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EURASIP Journal on Advances in Signal Processing |
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EURASIPJ |
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Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes. |
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1110-8657 |
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ISE |
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ISE @ ise @ MRR2010 |
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1208 |
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Author |
Pau Baiget |
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Title |
Modeling Human Behavior for Image Sequence Understanding and Generation |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The comprehension of animal behavior, especially human behavior, is one of the most ancient and studied problems since the beginning of civilization. The big list of factors that interact to determine a person action require the collaboration of different disciplines, such as psichology, biology, or sociology. In the last years the analysis of human behavior has received great attention also from the computer vision community, given the latest advances in the acquisition of human motion data from image sequences.
Despite the increasing availability of that data, there still exists a gap towards obtaining a conceptual representation of the obtained observations. Human behavior analysis is based on a qualitative interpretation of the results, and therefore the assignment of concepts to quantitative data is linked to a certain ambiguity.
This Thesis tackles the problem of obtaining a proper representation of human behavior in the contexts of computer vision and animation. On the one hand, a good behavior model should permit the recognition and explanation the observed activity in image sequences. On the other hand, such a model must allow the generation of new synthetic instances, which model the behavior of virtual agents.
First, we propose methods to automatically learn the models from observations. Given a set of quantitative results output by a vision system, a normal behavior model is learnt. This results provides a tool to determine the normality or abnormality of future observations. However, machine learning methods are unable to provide a richer description of the observations. We confront this problem by means of a new method that incorporates prior knowledge about the enviornment and about the expected behaviors. This framework, formed by the reasoning engine FMTL and the modeling tool SGT allows the generation of conceptual descriptions of activity in new image sequences. Finally, we demonstrate the suitability of the proposed framework to simulate behavior of virtual agents, which are introduced into real image sequences and interact with observed real agents, thereby easing the generation of augmented reality sequences.
The set of approaches presented in this Thesis has a growing set of potential applications. The analysis and description of behavior in image sequences has its principal application in the domain of smart video--surveillance, in order to detect suspicious or dangerous behaviors. Other applications include automatic sport commentaries, elderly monitoring, road traffic analysis, and the development of semantic video search engines. Alternatively, behavioral virtual agents allow to simulate accurate real situations, such as fires or crowds. Moreover, the inclusion of virtual agents into real image sequences has been widely deployed in the games and cinema industries. |
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Bellaterra (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Jordi Gonzalez;Xavier Roca |
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no |
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Call Number |
Admin @ si @ Bai2009 |
Serial |
1210 |
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Author |
Marco Pedersoli; Jordi Gonzalez; Juan J. Villanueva |
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Title |
High-Speed Human Detection Using a Multiresolution Cascade of Histograms of Oriented Gradients |
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Conference Article |
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2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of the detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a Support Vector Machine (SVM) composed by features at different resolution, from coarse for the first level to fine for the last one.
Considering that the spatial stride of the sliding window search is affected by the HOG features size, unlike previous methods based on Adaboost cascades, we can adopt a spatial stride inversely proportional to the features resolution. This produces that the speed-up of the cascade is not only due to the low number of features that need to be computed in the first levels, but also to the lower number of detection windows that needs to be evaluated.
Experimental results shows that our method permits a detection rate comparable with the state of the art, but at the same time a gain in the speed of the detection search of 10-20 times depending on the cascade configuration. |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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ISE |
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no |
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ISE @ ise @ PGV2009 |
Serial |
1214 |
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Author |
Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez |
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Title |
Towards Real-Time Human Action Recognition |
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Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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This work presents a novel approach to human detection based action-recognition in real-time. To realize this goal our method first detects humans in different poses using a correlation-based approach. Recognition of actions is done afterward based on the change of the angular values subtended by various body parts. Real-time human detection and action recognition are very challenging, and most state-of-the-art approaches employ complex feature extraction and classification techniques, which ultimately becomes a handicap for real-time recognition. Our correlation-based method, on the other hand, is computationally efficient and uses very simple gradient-based features. For action recognition angular features of body parts are extracted using a skeleton technique. Results for action recognition are comparable with the present state-of-the-art. |
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Póvoa de Varzim, Portugal |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-02171-8 |
Medium |
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Area |
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Expedition |
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Conference |
IbPRIA |
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Notes |
ISE |
Approved |
no |
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Call Number |
DAG @ dag @ CBG2009 |
Serial |
1215 |
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