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Aura Hernandez-Sabate; Jose Elias Yauri; Pau Folch; Daniel Alvarez; Debora Gil |
![goto web page url](http://refbase.cvc.uab.es/img/www.gif)
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Title |
EEG Dataset Collection for Mental Workload Predictions in Flight-Deck Environment |
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Journal Article |
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Year |
2024 |
Publication |
Sensors |
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SENS |
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24 |
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4 |
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1174 |
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High mental workload reduces human performance and the ability to correctly carry out complex tasks. In particular, aircraft pilots enduring high mental workloads are at high risk of failure, even with catastrophic outcomes. Despite progress, there is still a lack of knowledge about the interrelationship between mental workload and brain functionality, and there is still limited data on flight-deck scenarios. Although recent emerging deep-learning (DL) methods using physiological data have presented new ways to find new physiological markers to detect and assess cognitive states, they demand large amounts of properly annotated datasets to achieve good performance. We present a new dataset of electroencephalogram (EEG) recordings specifically collected for the recognition of different levels of mental workload. The data were recorded from three experiments, where participants were induced to different levels of workload through tasks of increasing cognition demand. The first involved playing the N-back test, which combines memory recall with arithmetical skills. The second was playing Heat-the-Chair, a serious game specifically designed to emphasize and monitor subjects under controlled concurrent tasks. The third was flying in an Airbus320 simulator and solving several critical situations. The design of the dataset has been validated on three different levels: (1) correlation of the theoretical difficulty of each scenario to the self-perceived difficulty and performance of subjects; (2) significant difference in EEG temporal patterns across the theoretical difficulties and (3) usefulness for the training and evaluation of AI models. |
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IAM |
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Admin @ si @ HYF2024 |
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4019 |
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Author |
Saad Minhas; Zeba Khanam; Shoaib Ehsan; Klaus McDonald Maier; Aura Hernandez-Sabate |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
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Title |
Weather Classification by Utilizing Synthetic Data |
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Journal Article |
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2022 |
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Sensors |
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SENS |
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22 |
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9 |
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3193 |
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Weather classification; synthetic data; dataset; autonomous car; computer vision; advanced driver assistance systems; deep learning; intelligent transportation systems |
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Weather prediction from real-world images can be termed a complex task when targeting classification using neural networks. Moreover, the number of images throughout the available datasets can contain a huge amount of variance when comparing locations with the weather those images are representing. In this article, the capabilities of a custom built driver simulator are explored specifically to simulate a wide range of weather conditions. Moreover, the performance of a new synthetic dataset generated by the above simulator is also assessed. The results indicate that the use of synthetic datasets in conjunction with real-world datasets can increase the training efficiency of the CNNs by as much as 74%. The article paves a way forward to tackle the persistent problem of bias in vision-based datasets. |
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21 April 2022 |
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MDPI |
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IAM; 600.139; 600.159; 600.166; 600.145; |
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Admin @ si @ MKE2022 |
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3761 |
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Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
A Deterministic-Statistic Adventitia Detection in IVUS Images |
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Conference Article |
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2005 |
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ESC Congress |
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Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation |
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Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles. |
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Stockholm; Sweden; September 2005 |
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,Sweden (EU) |
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IAM;MILAB |
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IAM @ iam @ RMF2005a |
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1523 |
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Author |
Aura Hernandez-Sabate |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Automatic adventitia segmentation in IntraVascular UltraSound images |
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Report |
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2005 |
Publication |
CVC Technical Report |
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85 |
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A usual tool in cardiac disease diagnosis is vessel plaque assessment by analysis of IVUS sequences. Manual detection of lumen-intima, intima-media and media-adventitia vessel borders is the main activity of physicians in the process of plaque quantification. Large variety in vessel border descriptors, as well as, shades, artifacts and blurred response due to ultrasound physical properties troubles automated media-adventitia segmentation. This experimental work presents a solution to such a complex problem. The process blends advanced anisotropic filtering operators and statistic classification techniques, achieving an efficient vessel border modelling strategy. First of all, we introduce the theoretic base of the method. After that, we show the steps of the algorithm, validating the method with statistics that show that the media-adventitia border detection achieves an accuracy in the range of inter-observer variability regardless of plaque nature, vessel geometry and incomplete vessel borders. Finally, we present a little Matlab application to the automatic media-adventitia border. |
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Master's thesis |
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08193 Bellaterra, Barcelona (Spain) |
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IAM; |
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IAM @ iam @ Her2005 |
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1544 |
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Author |
Aura Hernandez-Sabate; Debora Gil; Petia Radeva |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging |
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Conference Article |
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2005 |
Publication |
Proceeding of the 2005 conference on Artificial Intelligence Research and Development |
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67-74 |
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classification; vessel border modelling; IVUS |
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IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability. |
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IOS Press |
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Amsterdam, The Netherlands |
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IAM;MILAB |
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IAM @ iam @ HGR2005c |
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1549 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
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Conference Article |
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2011 |
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IEEE International Conference on Computer Vision – Workshops |
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2042-2049 |
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IEEE International Conference on Computer Vision – Workshops |
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Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
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IEEE |
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Barcelona (Spain) |
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English |
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English |
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ICCVW |
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IAM; ADAS |
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IAM @ iam @ MGH2011 |
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1682 |
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Author |
Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie |
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Title |
Inferring the Performance of Medical Imaging Algorithms |
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Conference Article |
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2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
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6854 |
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520-528 |
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Validation, Statistical Inference, Medical Imaging Algorithms. |
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Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence. |
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Sevilla |
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Springer-Verlag Berlin Heidelberg |
Place of Publication ![sorted by Place of Publication field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Berlin |
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Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch |
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CAIP |
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IAM; ADAS |
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IAM @ iam @ HGR2011 |
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1676 |
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Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias |
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Title |
Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images |
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Conference Article |
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Year |
2004 |
Publication |
Proc. Computers in Cardiology |
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31 |
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229-232 |
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The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles |
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Chicago (USA) |
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IAM; MILAB |
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IAM @ iam @ HGR2004 |
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1555 |
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Author |
Aura Hernandez-Sabate; Petia Radeva; Antonio Tovar; Debora Gil |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Vessel structures alignment by spectral analysis of ivus sequences |
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Conference Article |
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2006 |
Publication |
Proc. of CVII, MICCAI Workshop |
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39-36 |
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Three-dimensional intravascular ultrasound (IVUS) allows to visualize and obtain volumetric measurements of coronary lesions through an exploration of the cross sections and longitudinal views of arteries. However, the visualization and subsequent morpho-geometric measurements in IVUS longitudinal cuts are subject to distortion caused by periodic image/vessel motion around the IVUS catheter. Usually, to overcome the image motion artifact ECG-gating and image-gated approaches are proposed, leading to slowing the pullback acquisition or disregarding part of IVUS data. In this paper, we argue that the image motion is due to 3-D vessel geometry as well as cardiac dynamics, and propose a dynamic model based on the tracking of an elliptical vessel approximation to recover the rigid transformation and align IVUS images without loosing any IVUS data. We report an extensive validation with synthetic simulated data and in vivo IVUS sequences of 30 patients achieving an average reduction of the image artifact of 97% in synthetic data and 79% in real-data. Our study shows that IVUS alignment improves longitudinal analysis of the IVUS data and is a necessary step towards accurate reconstruction and volumetric measurements of 3-D IVUS. |
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Copenhaguen (Denmark), |
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1st International Wokshop on Computer Vision for Intravascular and Intracardiac Imaging (CVII’06) |
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IAM; MILAB |
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IAM @ iam @ HRT2006 |
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1552 |
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F.Guirado; Ana Ripoll; C.Roig; Aura Hernandez-Sabate; Emilio Luque |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Exploiting Throughput for Pipeline Execution in Streaming Image Processing Applications |
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Book Chapter |
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2006 |
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Euro-Par 2006 Parallel Processing |
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LNCS |
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4128 |
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1095-1105 |
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12th International Euro–Par Conference |
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There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when execu- ting them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodo- logy we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate. |
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Springer-Verlag Berlin Heidelberg |
Place of Publication ![sorted by Place of Publication field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Dresden, Germany (European Union) |
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UAB; W, E.N.; et al. |
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Lecture Notes In Computer Science |
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IAM |
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IAM @ iam @ GRR2006a |
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1542 |
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