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Author | Frederic Sampedro; Anna Domenech; Sergio Escalera; Ignasi Carrio | ||||
Title | Deriving global quantitative tumor response parameters from 18F-FDG PET-CT scans in patients with non-Hodgkins lymphoma | Type | Journal Article | ||
Year | 2015 | Publication | Nuclear Medicine Communications | Abbreviated Journal | NMC |
Volume | 36 | Issue | 4 | Pages | 328-333 |
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Abstract | OBJECTIVES:
The aim of the study was to address the need for quantifying the global cancer time evolution magnitude from a pair of time-consecutive positron emission tomography-computed tomography (PET-CT) scans. In particular, we focus on the computation of indicators using image-processing techniques that seek to model non-Hodgkin's lymphoma (NHL) progression or response severity. MATERIALS AND METHODS: A total of 89 pairs of time-consecutive PET-CT scans from NHL patients were stored in a nuclear medicine station for subsequent analysis. These were classified by a consensus of nuclear medicine physicians into progressions, partial responses, mixed responses, complete responses, and relapses. The cases of each group were ordered by magnitude following visual analysis. Thereafter, a set of quantitative indicators designed to model the cancer evolution magnitude within each group were computed using semiautomatic and automatic image-processing techniques. Performance evaluation of the proposed indicators was measured by a correlation analysis with the expert-based visual analysis. RESULTS: The set of proposed indicators achieved Pearson's correlation results in each group with respect to the expert-based visual analysis: 80.2% in progressions, 77.1% in partial response, 68.3% in mixed response, 88.5% in complete response, and 100% in relapse. In the progression and mixed response groups, the proposed indicators outperformed the common indicators used in clinical practice [changes in metabolic tumor volume, mean, maximum, peak standardized uptake value (SUV mean, SUV max, SUV peak), and total lesion glycolysis] by more than 40%. CONCLUSION: Computing global indicators of NHL response using PET-CT imaging techniques offers a strong correlation with the associated expert-based visual analysis, motivating the future incorporation of such quantitative and highly observer-independent indicators in oncological decision making or treatment response evaluation scenarios. |
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Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ SDE2015 | Serial | 2605 | ||
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Author | Jiaolong Xu | ||||
Title | Domain Adaptation of Deformable Part-based Models | Type | Book Whole | ||
Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | On-board pedestrian detection is crucial for Advanced Driver Assistance Systems
(ADAS). An accurate classication is fundamental for vision-based pedestrian detection. The underlying assumption for learning classiers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classiers. However, in practice, there are dierent reasons that can break this constancy assumption. Accordingly, reusing existing classiers by adapting them from the previous training environment (source domain) to the new testing one (target domain) is an approach with increasing acceptance in the computer vision community. In this thesis we focus on the domain adaptation of deformable part-based models (DPMs) for pedestrian detection. As a prof of concept, we use a computer graphic based synthetic dataset, i.e. a virtual world, as the source domain, and adapt the virtual-world trained DPM detector to various real-world dataset. We start by exploiting the maximum detection accuracy of the virtual-world trained DPM. Even though, when operating in various real-world datasets, the virtualworld trained detector still suer from accuracy degradation due to the domain gap of virtual and real worlds. We then focus on domain adaptation of DPM. At the rst step, we consider single source and single target domain adaptation and propose two batch learning methods, namely A-SSVM and SA-SSVM. Later, we further consider leveraging multiple target (sub-)domains for progressive domain adaptation and propose a hierarchical adaptive structured SVM (HA-SSVM) for optimization. Finally, we extend HA-SSVM for the challenging online domain adaptation problem, aiming at making the detector to automatically adapt to the target domain online, without any human intervention. All of the proposed methods in this thesis do not require revisiting source domain data. The evaluations are done on the Caltech pedestrian detection benchmark. Results show that SA-SSVM slightly outperforms A-SSVM and avoids accuracy drops as high as 15 points when comparing with a non-adapted detector. The hierarchical model learned by HA-SSVM further boosts the domain adaptation performance. Finally, the online domain adaptation method has demonstrated that it can achieve comparable accuracy to the batch learned models while not requiring manually label target domain examples. Domain adaptation for pedestrian detection is of paramount importance and a relatively unexplored area. We humbly hope the work in this thesis could provide foundations for future work in this area. |
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Address | April 2015 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Place of Publication | Editor | Antonio Lopez | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-84-943427-1-4 | Medium | ||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ Xu2015 | Serial | 2631 | ||
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Author | Patricia Marquez | ||||
Title | A Confidence Framework for the Assessment of Optical Flow Performance | Type | Book Whole | ||
Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | Optical Flow (OF) is the input of a wide range of decision support systems such as car driver assistance, UAV guiding or medical diagnose. In these real situations, the absence of ground truth forces to assess OF quality using quantities computed from either sequences or the computed optical flow itself. These quantities are generally known as Confidence Measures, CM. Even if we have a proper confidence measure we still need a way to evaluate its ability to discard pixels with an OF prone to have a large error. Current approaches only provide a descriptive evaluation of the CM performance but such approaches are not capable to fairly compare different confidence measures and optical flow algorithms. Thus, it is of prime importance to define a framework and a general road map for the evaluation of optical flow performance.
This thesis provides a framework able to decide which pairs “ optical flow – confidence measure” (OF-CM) are best suited for optical flow error bounding given a confidence level determined by a decision support system. To design this framework we cover the following points: Descriptive scores. As a first step, we summarize and analyze the sources of inaccuracies in the output of optical flow algorithms. Second, we present several descriptive plots that visually assess CM capabilities for OF error bounding. In addition to the descriptive plots, given a plot representing OF-CM capabilities to bound the error, we provide a numeric score that categorizes the plot according to its decreasing profile, that is, a score assessing CM performance. Statistical framework. We provide a comparison framework that assesses the best suited OF-CM pair for error bounding that uses a two stage cascade process. First of all we assess the predictive value of the confidence measures by means of a descriptive plot. Then, for a sample of descriptive plots computed over training frames, we obtain a generic curve that will be used for sequences with no ground truth. As a second step, we evaluate the obtained general curve and its capabilities to really reflect the predictive value of a confidence measure using the variability across train frames by means of ANOVA. The presented framework has shown its potential in the application on clinical decision support systems. In particular, we have analyzed the impact of the different image artifacts such as noise and decay to the output of optical flow in a cardiac diagnose system and we have improved the navigation inside the bronchial tree on bronchoscopy. |
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Address | July 2015 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Debora Gil;Aura Hernandez | |
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ISSN | ISBN | 978-84-943427-2-1 | Medium | ||
Area | Expedition | Conference | |||
Notes | IAM; 600.075 | Approved | no | ||
Call Number | Admin @ si @ Mar2015 | Serial | 2687 | ||
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Author | Miguel Oliveira; Victor Santos; Angel Sappa | ||||
Title | Multimodal Inverse Perspective Mapping | Type | Journal Article | ||
Year | 2015 | Publication | Information Fusion | Abbreviated Journal | IF |
Volume | 24 | Issue | Pages | 108–121 | |
Keywords | Inverse perspective mapping; Multimodal sensor fusion; Intelligent vehicles | ||||
Abstract | Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints. | ||||
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Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ OSS2015c | Serial | 2532 | ||
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Author | Ramin Irani; Kamal Nasrollahi; Chris Bahnsen; D.H. Lundtoft; Thomas B. Moeslund; Marc O. Simon; Ciprian Corneanu; Sergio Escalera; Tanja L. Pedersen; Maria-Louise Klitgaard; Laura Petrini | ||||
Title | Spatio-temporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition | Type | Conference Article | ||
Year | 2015 | Publication | 2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) | Abbreviated Journal | |
Volume | Issue | Pages | 88-95 | ||
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Abstract | Pain is a vital sign of human health and its automatic detection can be of crucial importance in many different contexts, including medical scenarios. While most available computer vision techniques are based on RGB, in this paper, we investigate the effect of combining RGB, depth, and thermal
facial images for pain detection and pain intensity level recognition. For this purpose, we extract energies released by facial pixels using a spatiotemporal filter. Experiments on a group of 12 elderly people applying the multimodal approach show that the proposed method successfully detects pain and recognizes between three intensity levels in 82% of the analyzed frames improving more than 6% over RGB only analysis in similar conditions. |
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Address | Boston; EEUU; June 2015 | ||||
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Area | Expedition | Conference | CVPRW | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ INB2015 | Serial | 2654 | ||
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Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
Title | Combining Local and Global Learners in the Pairwise Multiclass Classification | Type | Journal Article | ||
Year | 2015 | Publication | Pattern Analysis and Applications | Abbreviated Journal | PAA |
Volume | 18 | Issue | 4 | Pages | 845-860 |
Keywords | Multiclass classification; Pairwise approach; One-versus-one | ||||
Abstract | Pairwise classification is a well-known class binarization technique that converts a multiclass problem into a number of two-class problems, one problem for each pair of classes. However, in the pairwise technique, nuisance votes of many irrelevant classifiers may result in a wrong class prediction. To overcome this problem, a simple, but efficient method is proposed and evaluated in this paper. The proposed method is based on excluding some classes and focusing on the most probable classes in the neighborhood space, named Local Crossing Off (LCO). This procedure is performed by employing a modified version of standard K-nearest neighbor and large margin nearest neighbor algorithms. The LCO method takes advantage of nearest neighbor classification algorithm because of its local learning behavior as well as the global behavior of powerful binary classifiers to discriminate between two classes. Combining these two properties in the proposed LCO technique will avoid the weaknesses of each method and will increase the efficiency of the whole classification system. On several benchmark datasets of varying size and difficulty, we found that the LCO approach leads to significant improvements using different base learners. The experimental results show that the proposed technique not only achieves better classification accuracy in comparison to other standard approaches, but also is computationally more efficient for tackling classification problems which have a relatively large number of target classes. | ||||
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Publisher | Springer London | Place of Publication | Editor | ||
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ISSN | 1433-7541 | ISBN | Medium | ||
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Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BGE2014 | Serial | 2441 | ||
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Author | Alejandro Gonzalez Alzate; Sebastian Ramos; David Vazquez; Antonio Lopez; Jaume Amores | ||||
Title | Spatiotemporal Stacked Sequential Learning for Pedestrian Detection | Type | Conference Article | ||
Year | 2015 | Publication | Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 | Abbreviated Journal | |
Volume | Issue | Pages | 3-12 | ||
Keywords | SSL; Pedestrian Detection | ||||
Abstract | Pedestrian classifiers decide which image windows contain a pedestrian. In practice, such classifiers provide a relatively high response at neighbor windows overlapping a pedestrian, while the responses around potential false positives are expected to be lower. An analogous reasoning applies for image sequences. If there is a pedestrian located within a frame, the same pedestrian is expected to appear close to the same location in neighbor frames. Therefore, such a location has chances of receiving high classification scores during several frames, while false positives are expected to be more spurious. In this paper we propose to exploit such correlations for improving the accuracy of base pedestrian classifiers. In particular, we propose to use two-stage classifiers which not only rely on the image descriptors required by the base classifiers but also on the response of such base classifiers in a given spatiotemporal neighborhood. More specifically, we train pedestrian classifiers using a stacked sequential learning (SSL) paradigm. We use a new pedestrian dataset we have acquired from a car to evaluate our proposal at different frame rates. We also test on a well known dataset: Caltech. The obtained results show that our SSL proposal boosts detection accuracy significantly with a minimal impact on the computational cost. Interestingly, SSL improves more the accuracy at the most dangerous situations, i.e. when a pedestrian is close to the camera. | ||||
Address | Santiago de Compostela; España; June 2015 | ||||
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Area | ACDC | Expedition | Conference | IbPRIA | |
Notes | ADAS; 600.057; 600.054; 600.076 | Approved | no | ||
Call Number | GRV2015; ADAS @ adas @ GRV2015 | Serial | 2454 | ||
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Author | Alejandro Gonzalez Alzate | ||||
Title | Multi-modal Pedestrian Detection | Type | Book Whole | ||
Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | Pedestrian detection continues to be an extremely challenging problem in real scenarios, in which situations like illumination changes, noisy images, unexpected objects, uncontrolled scenarios and variant appearance of objects occur constantly. All these problems force the development of more robust detectors for relevant applications like vision-based autonomous vehicles, intelligent surveillance, and pedestrian tracking for behavior analysis. Most reliable vision-based pedestrian detectors base their decision on features extracted using a single sensor capturing complementary features, e.g., appearance, and texture. These features usually are extracted from the current frame, ignoring temporal information, or including it in a post process step e.g., tracking or temporal coherence. Taking into account these issues we formulate the following question: can we generate more robust pedestrian detectors by introducing new information sources in the feature extraction step?
In order to answer this question we develop different approaches for introducing new information sources to well-known pedestrian detectors. We start by the inclusion of temporal information following the Stacked Sequential Learning (SSL) paradigm which suggests that information extracted from the neighboring samples in a sequence can improve the accuracy of a base classifier. We then focus on the inclusion of complementary information from different sensors like 3D point clouds (LIDAR – depth), far infrared images (FIR), or disparity maps (stereo pair cameras). For this end we develop a multi-modal framework in which information from different sensors is used for increasing detection accuracy (by increasing information redundancy). Finally we propose a multi-view pedestrian detector, this multi-view approach splits the detection problem in n sub-problems. Each sub-problem will detect objects in a given specific view reducing in that way the variability problem faced when a single detectors is used for the whole problem. We show that these approaches obtain competitive results with other state-of-the-art methods but instead of design new features, we reuse existing ones boosting their performance. |
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Address | November 2015 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | David Vazquez;Antonio Lopez; | |
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ISSN | ISBN | 978-84-943427-7-6 | Medium | ||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ Gon2015 | Serial | 2706 | ||
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Author | Victor Campmany; Sergio Silva; Juan Carlos Moure; Antoni Espinosa; David Vazquez; Antonio Lopez | ||||
Title | GPU-based pedestrian detection for autonomous driving | Type | Abstract | ||
Year | 2015 | Publication | Programming and Tunning Massive Parallel Systems | Abbreviated Journal | PUMPS |
Volume | Issue | Pages | |||
Keywords | Autonomous Driving; ADAS; CUDA; Pedestrian Detection | ||||
Abstract | Pedestrian detection for autonomous driving has gained a lot of prominence during the last few years. Besides the fact that it is one of the hardest tasks within computer vision, it involves huge computational costs. The real-time constraints in the field are tight, and regular processors are not able to handle the workload obtaining an acceptable ratio of frames per second (fps). Moreover, multiple cameras are required to obtain accurate results, so the need to speed up the process is even higher. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system. Further, we introduce significant algorithmic adjustments and optimizations to adapt the problem to the GPU architecture. The aim is to provide a system capable of running in real-time obtaining reliable results. | ||||
Address | Barcelona; Spain | ||||
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Series Editor | Series Title | Abbreviated Series Title | PUMPS | ||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | PUMPS | ||
Notes | ADAS; 600.076; 600.082; 600.085 | Approved | no | ||
Call Number | ADAS @ adas @ CSM2015 | Serial | 2644 | ||
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Author | Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil | ||||
Title | A Novel Cochlear Reference Frame Based On The Laplace Equation | Type | Conference Article | ||
Year | 2015 | Publication | 29th international Congress and Exhibition on Computer Assisted Radiology and Surgery | Abbreviated Journal | |
Volume | 10 | Issue | 1 | Pages | 1-312 |
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Abstract | Poster | ||||
Address | Barcelona; Spain; June 2015 | ||||
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Area | Expedition | Conference | CARS | ||
Notes | IAM; 600.075 | Approved | no | ||
Call Number | Admin @ si @ VGG2015 | Serial | 2615 | ||
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Author | Arash Akbarinia; C. Alejandro Parraga | ||||
Title | Biologically Plausible Colour Naming Model | Type | Conference Article | ||
Year | 2015 | Publication | European Conference on Visual Perception ECVP2015 | Abbreviated Journal | |
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Address | Liverpool; UK; August 2015 | ||||
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Area | Expedition | Conference | ECVP | ||
Notes | NEUROBIT; 600.068 | Approved | no | ||
Call Number | Admin @ si @ AkP2015 | Serial | 2660 | ||
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Author | Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich | ||||
Title | DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition | Type | Conference Article | ||
Year | 2015 | Publication | Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II | Abbreviated Journal | |
Volume | 9475 | Issue | Pages | 463-473 | |
Keywords | Projector-camera systems; Feature descriptors; Object recognition | ||||
Abstract | Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection. | ||||
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Publisher | Springer International Publishing | Place of Publication | Editor | ||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-319-27862-9 | Medium | |
Area | Expedition | Conference | ISVC | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ SMG2015 | Serial | 2736 | ||
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Author | Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell; Debora Gil | ||||
Title | Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy | Type | Conference Article | ||
Year | 2015 | Publication | 6th International Conference on Information Processing in Computer-Assisted Interventions IPCAI2015 | Abbreviated Journal | |
Volume | 10 | Issue | 6 | Pages | 935-945 |
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Abstract | PURPOSE:
Lack of objective measurement of tracheal obstruction degree has a negative impact on the chosen treatment prone to lead to unnecessary repeated explorations and other scanners. Accurate computation of tracheal stenosis in videobronchoscopy would constitute a breakthrough for this noninvasive technique and a reduction in operation cost for the public health service. METHODS: Stenosis calculation is based on the comparison of the region delimited by the lumen in an obstructed frame and the region delimited by the first visible ring in a healthy frame. We propose a parametric strategy for the extraction of lumen and tracheal ring regions based on models of their geometry and appearance that guide a deformable model. To ensure a systematic applicability, we present a statistical framework to choose optimal parametric values and a strategy to choose the frames that minimize the impact of scope optical distortion. RESULTS: Our method has been tested in 40 cases covering different stenosed tracheas. Experiments report a non- clinically relevant [Formula: see text] of discrepancy in the calculated stenotic area and a computational time allowing online implementation in the operating room. CONCLUSIONS: Our methodology allows reliable measurements of airway narrowing in the operating room. To fully assess its clinical impact, a prospective clinical trial should be done. |
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Address | Barcelona; Spain; June 2015 | ||||
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Area | Expedition | Conference | IPCAI | ||
Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | Admin @ si @ SBS2015b | Serial | 2613 | ||
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Author | Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach | ||||
Title | Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists | Type | Book Chapter | ||
Year | 2015 | Publication | Colonoscopy and Colorectal Cancer | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description | ||||
Abstract | Recent advances in endoscopic technology have generated an increasing interest in strengthening the collaboration between clinicians and computers scientist to develop intelligent systems that can provide additional information to clinicians in the different stages of an intervention. The objective of this chapter is to identify clinical drawbacks of colonoscopy in order to define potential areas of collaboration. Once areas are defined, we present the challenges that colonoscopy images present in order computational methods to provide with meaningful output, including those related to image formation and acquisition, as they are proven to have an impact in the performance of an intelligent system. Finally, we also propose how to define validation frameworks in order to assess the performance of a given method, making an special emphasis on how databases should be created and annotated and which metrics should be used to evaluate systems correctly. | ||||
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ISSN | ISBN | 978-953-51-2225-8 | Medium | ||
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Notes | MV | Approved | no | ||
Call Number | Admin @ si @ BSR2015 | Serial | 2624 | ||
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Author | Lluis Pere de las Heras; Oriol Ramos Terrades; Sergi Robles; Gemma Sanchez | ||||
Title | CVC-FP and SGT: a new database for structural floor plan analysis and its groundtruthing tool | Type | Journal Article | ||
Year | 2015 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
Volume | 18 | Issue | 1 | Pages | 15-30 |
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Abstract | Recent results on structured learning methods have shown the impact of structural information in a wide range of pattern recognition tasks. In the field of document image analysis, there is a long experience on structural methods for the analysis and information extraction of multiple types of documents. Yet, the lack of conveniently annotated and free access databases has not benefited the progress in some areas such as technical drawing understanding. In this paper, we present a floor plan database, named CVC-FP, that is annotated for the architectural objects and their structural relations. To construct this database, we have implemented a groundtruthing tool, the SGT tool, that allows to make specific this sort of information in a natural manner. This tool has been made for general purpose groundtruthing: It allows to define own object classes and properties, multiple labeling options are possible, grants the cooperative work, and provides user and version control. We finally have collected some of the recent work on floor plan interpretation and present a quantitative benchmark for this database. Both CVC-FP database and the SGT tool are freely released to the research community to ease comparisons between methods and boost reproducible research. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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ISSN | 1433-2833 | ISBN | Medium | ||
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Notes | DAG; ADAS; 600.061; 600.076; 600.077 | Approved | no | ||
Call Number | Admin @ si @ HRR2015 | Serial | 2567 | ||
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