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Author | Fernando Vilariño; Gerard Lacey | ||||
Title | QUALITY ASSESSMENT IN COLONOSCOPY New challenges through computer vision-based systems | Type | Conference Article | ||
Year | 2009 | Publication | in Proc. 3rd International Conference on Biomedical Electronics and Devices | Abbreviated Journal | |
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Area | 800 | Expedition | Conference | ||
Notes | MV;SIAI | Approved | no | ||
Call Number | fernando @ fernando @ | Serial | 2430 | ||
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Author | Fernando Vilariño; Gerard Lacey; Jiang Zhou; Hugh Mulcahy; Stephen Patchett | ||||
Title | Automatic Labeling of Colonoscopy Video for Cancer Detection | Type | Conference Article | ||
Year | 2007 | Publication | In Proc. berian Conference, IbPRIA | Abbreviated Journal | |
Volume | Issue | Pages | 290-297 | ||
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Area | 800 | Expedition | Conference | ||
Notes | MV;SIAI | Approved | no | ||
Call Number | fernando @ fernando @ | Serial | 2431 | ||
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Author | Jiaolong Xu; Sebastian Ramos;David Vazquez; Antonio Lopez | ||||
Title | Cost-sensitive Structured SVM for Multi-category Domain Adaptation | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 3886 - 3891 | ||
Keywords | Domain Adaptation; Pedestrian Detection | ||||
Abstract | Domain adaptation addresses the problem of accuracy drop that a classifier may suffer when the training data (source domain) and the testing data (target domain) are drawn from different distributions. In this work, we focus on domain adaptation for structured SVM (SSVM). We propose a cost-sensitive domain adaptation method for SSVM, namely COSS-SSVM. In particular, during the re-training of an adapted classifier based on target and source data, the idea that we explore consists in introducing a non-zero cost even for correctly classified source domain samples. Eventually, we aim to learn a more targetoriented classifier by not rewarding (zero loss) properly classified source-domain training samples. We assess the effectiveness of COSS-SSVM on multi-category object recognition. | ||||
Address | Stockholm; Sweden; August 2014 | ||||
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Publisher | IEEE | Place of Publication | Editor | ||
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ISSN | 1051-4651 | ISBN | Medium | ||
Area | Expedition | Conference | ICPR | ||
Notes | ADAS; 600.057; 600.054; 601.217; 600.076 | Approved | no | ||
Call Number | ADAS @ adas @ XRV2014a | Serial | 2434 | ||
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Author | Katerine Diaz; Francesc J. Ferri | ||||
Title | Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes | Type | Book Whole | ||
Year | 2013 | Publication | Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes | Abbreviated Journal | |
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Abstract | Los métodos basados en subespacios son una herramienta muy utilizada en aplicaciones de visión por computador. Aquí se presentan y validan algunos algoritmos que hemos propuesto en este campo de investigación. El primer algoritmo está relacionado con una extensión del método de vectores comunes discriminantes con kernel, que reinterpreta el espacio nulo de la matriz de dispersión intra-clase del conjunto de entrenamiento para obtener las características discriminantes. Dentro de los métodos basados en subespacios existen diferentes tipos de entrenamiento. Uno de los más populares, pero no por ello uno de los más eficientes, es el aprendizaje por lotes. En este tipo de aprendizaje, todas las muestras del conjunto de entrenamiento tienen que estar disponibles desde el inicio. De este modo, cuando nuevas muestras se ponen a disposición del algoritmo, el sistema tiene que ser reentrenado de nuevo desde cero. Una alternativa a este tipo de entrenamiento es el aprendizaje incremental. Aquí se proponen diferentes algoritmos incrementales del método de vectores comunes discriminantes. | ||||
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ISSN | ISBN | 978-3-639-55339-0 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ DiF2013 | Serial | 2440 | ||
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Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
Title | Generic Subclass Ensemble: A Novel Approach to Ensemble Classification | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1254 - 1259 | ||
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Abstract | Multiple classifier systems, also known as classifier ensembles, have received great attention in recent years because of their improved classification accuracy in different applications. In this paper, we propose a new general approach to ensemble classification, named generic subclass ensemble, in which each base classifier is trained with data belonging to a subset of classes, and thus discriminates among a subset of target categories. The ensemble classifiers are then fused using a combination rule. The proposed approach differs from existing methods that manipulate the target attribute, since in our approach individual classification problems are not restricted to two-class problems. We perform a series of experiments to evaluate the efficiency of the generic subclass approach on a set of benchmark datasets. Experimental results with multilayer perceptrons show that the proposed approach presents a viable alternative to the most commonly used ensemble classification approaches. | ||||
Address | Stockholm; August 2014 | ||||
Corporate Author | Thesis | ||||
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ISSN | 1051-4651 | ISBN | Medium | ||
Area | Expedition | Conference | ICPR | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BGE2014b | Serial | 2445 | ||
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Author | Mohammad Ali Bagheri; Gang Hu; Qigang Gao; Sergio Escalera | ||||
Title | A Framework of Multi-Classifier Fusion for Human Action Recognition | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1260 - 1265 | ||
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Abstract | The performance of different action-recognition methods using skeleton joint locations have been recently studied by several computer vision researchers. However, the potential improvement in classification through classifier fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of five action learning techniques, each performing the recognition task from a different perspective. The underlying rationale of the fusion approach is that different learners employ varying structures of input descriptors/features to be trained. These varying structures cannot be attached and used by a single learner. In addition, combining the outputs of several learners can reduce the risk of an unfortunate selection of a poorly performing learner. This leads to having a more robust and general-applicable framework. Also, we propose two simple, yet effective, action description techniques. In order to improve the recognition performance, a powerful combination strategy is utilized based on the Dempster-Shafer theory, which can effectively make use of diversity of base learners trained on different sources of information. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers' output, showing advanced performance of the proposed methodology. | ||||
Address | Stockholm; Sweden; August 2014 | ||||
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ISSN | 1051-4651 | ISBN | Medium | ||
Area | Expedition | Conference | ICPR | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BHG2014 | Serial | 2446 | ||
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Author | Naveen Onkarappa | ||||
Title | Optical Flow in Driver Assistance Systems | Type | Book Whole | ||
Year | 2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | Motion perception is one of the most important attributes of the human brain. Visual motion perception consists in inferring speed and direction of elements in a scene based on visual inputs. Analogously, computer vision is assisted by motion cues in the scene. Motion detection in computer vision is useful in solving problems such as segmentation, depth from motion, structure from motion, compression, navigation and many others. These problems are common in several applications, for instance, video surveillance, robot navigation and advanced driver assistance systems (ADAS). One of the most widely used techniques for motion detection is the optical flow estimation. The work in this thesis attempts to make optical flow suitable for the requirements and conditions of driving scenarios. In this context, a novel space-variant representation called reverse log-polar representation is proposed that is shown to be better than the traditional log-polar space-variant representation for ADAS. The space-variant representations reduce the amount of data to be processed. Another major contribution in this research is related to the analysis of the influence of specific characteristics from driving scenarios on the optical flow accuracy. Characteristics such as vehicle speed and
road texture are considered in the aforementioned analysis. From this study, it is inferred that the regularization weight has to be adapted according to the required error measure and for different speeds and road textures. It is also shown that polar represented optical flow suits driving scenarios where predominant motion is translation. Due to the requirements of such a study and by the lack of needed datasets a new synthetic dataset is presented; it contains: i) sequences of different speeds and road textures in an urban scenario; ii) sequences with complex motion of an on-board camera; and iii) sequences with additional moving vehicles in the scene. The ground-truth optical flow is generated by the ray-tracing technique. Further, few applications of optical flow in ADAS are shown. Firstly, a robust RANSAC based technique to estimate horizon line is proposed. Then, an egomotion estimation is presented to compare the proposed space-variant representation with the classical one. As a final contribution, a modification in the regularization term is proposed that notably improves the results in the ADAS applications. This adaptation is evaluated using a state of the art optical flow technique. The experiments on a public dataset (KITTI) validate the advantages of using the proposed modification. |
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Address | Bellaterra | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Angel Sappa | |
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ISSN | ISBN | 978-84-940902-1-9 | Medium | ||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ Nav2013 | Serial | 2447 | ||
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Author | Jorge Bernal; Fernando Vilariño; F. Javier Sanchez; M. Arnold; Anarta Ghosh; Gerard Lacey | ||||
Title | Experts vs Novices: Applying Eye-tracking Methodologies in Colonoscopy Video Screening for Polyp Search | Type | Conference Article | ||
Year | 2014 | Publication | 2014 Symposium on Eye Tracking Research and Applications | Abbreviated Journal | |
Volume | Issue | Pages | 223-226 | ||
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Abstract | We present in this paper a novel study aiming at identifying the differences in visual search patterns between physicians of diverse levels of expertise during the screening of colonoscopy videos. Physicians were clustered into two groups -experts and novices- according to the number of procedures performed, and fixations were captured by an eye-tracker device during the task of polyp search in different video sequences. These fixations were integrated into heat maps, one for each cluster. The obtained maps were validated over a ground truth consisting of a mask of the polyp, and the comparison between experts and novices was performed by using metrics such as reaction time, dwelling time and energy concentration ratio. Experimental results show a statistically significant difference between experts and novices, and the obtained maps show to be a useful tool for the characterisation of the behaviour of each group. | ||||
Address | USA; March 2014 | ||||
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ISSN | ISBN | 978-1-4503-2751-0 | Medium | ||
Area | Expedition | Conference | ETRA | ||
Notes | MV; 600.047; 600.060;SIAI | Approved | no | ||
Call Number | Admin @ si @ BVS2014 | Serial | 2448 | ||
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Author | Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Michael Felsberg | ||||
Title | Scale Coding Bag-of-Words for Action Recognition | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1514-1519 | ||
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Abstract | Recognizing human actions in still images is a challenging problem in computer vision due to significant amount of scale, illumination and pose variation. Given the bounding box of a person both at training and test time, the task is to classify the action associated with each bounding box in an image.
Most state-of-the-art methods use the bag-of-words paradigm for action recognition. The bag-of-words framework employing a dense multi-scale grid sampling strategy is the de facto standard for feature detection. This results in a scale invariant image representation where all the features at multiple-scales are binned in a single histogram. We argue that such a scale invariant strategy is sub-optimal since it ignores the multi-scale information available with each bounding box of a person. This paper investigates alternative approaches to scale coding for action recognition in still images. We encode multi-scale information explicitly in three different histograms for small, medium and large scale visual-words. Our first approach exploits multi-scale information with respect to the image size. In our second approach, we encode multi-scale information relative to the size of the bounding box of a person instance. In each approach, the multi-scale histograms are then concatenated into a single representation for action classification. We validate our approaches on the Willow dataset which contains seven action categories: interacting with computer, photography, playing music, riding bike, riding horse, running and walking. Our results clearly suggest that the proposed scale coding approaches outperform the conventional scale invariant technique. Moreover, we show that our approach obtains promising results compared to more complex state-of-the-art methods. |
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Address | Stockholm; August 2014 | ||||
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Area | Expedition | Conference | ICPR | ||
Notes | CIC; LAMP; 601.240; 600.074; 600.079 | Approved | no | ||
Call Number | Admin @ si @ KWB2014 | Serial | 2450 | ||
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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 | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
Title | Incremental Domain Adaptation of Deformable Part-based Models | Type | Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Pedestrian Detection; Part-based models; Domain Adaptation | ||||
Abstract | Nowadays, classifiers play a core role in many computer vision tasks. The underlying assumption for learning classifiers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classifiers. However, in practice, there are different reasons that can break this constancy assumption. Accordingly, reusing existing classifiers 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 paper we focus on the domain adaptation of deformable part-based models (DPMs) for object detection. In particular, we focus on a relatively unexplored scenario, i.e. incremental domain adaptation for object detection assuming weak-labeling. Therefore, our algorithm is ready to improve existing source-oriented DPM-based detectors as soon as a little amount of labeled target-domain training data is available, and keeps improving as more of such data arrives in a continuous fashion. For achieving this, we follow a multiple instance learning (MIL) paradigm that operates in an incremental per-image basis. As proof of concept, we address the challenging scenario of adapting a DPM-based pedestrian detector trained with synthetic pedestrians to operate in real-world scenarios. The obtained results show that our incremental adaptive models obtain equally good accuracy results as the batch learned models, while being more flexible for handling continuously arriving target-domain data. |
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Address | Nottingham; uk; September 2014 | ||||
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Publisher | BMVA Press | Place of Publication | Editor | Valstar, Michel and French, Andrew and Pridmore, Tony | |
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Area | Expedition | Conference | BMVC | ||
Notes | ADAS; 600.057; 600.054; 600.076 | Approved | no | ||
Call Number | XRV2014c; ADAS @ adas @ xrv2014c | Serial | 2455 | ||
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Author | Enric Marti; Antoni Gurgui; Debora Gil; Aura Hernandez-Sabate; Jaume Rocarias; Ferran Poveda | ||||
Title | ABP on line: Seguimiento, estregas y evaluación en aprendizaje basado en proyectos | Type | Miscellaneous | ||
Year | 2014 | Publication | 8th International Congress on University Teaching and Innovation | Abbreviated Journal | |
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Address | Tarragona; juliol 2014 | ||||
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Area | Expedition | Conference | CIDUI | ||
Notes | IAM; ADAS; 600.076; 600.063; 600.075 | Approved | no | ||
Call Number | Admin @ si @ MGG2014 | Serial | 2457 | ||
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Author | Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; Jaume Rocarias; Debora Gil | ||||
Title | Evaluación automática de prácticas en Moodle para el aprendizaje autónomo en Ingenierías | Type | Miscellaneous | ||
Year | 2014 | Publication | 8th International Congress on University Teaching and Innovation | Abbreviated Journal | |
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Address | Tarragona; juliol 2014 | ||||
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Area | Expedition | Conference | CIDUI | ||
Notes | IAM; 600.075;DAG | Approved | no | ||
Call Number | Admin @ si @ SRM2014 | Serial | 2458 | ||
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Author | David Fernandez; Pau Riba; Alicia Fornes; Josep Llados | ||||
Title | On the Influence of Key Point Encoding for Handwritten Word Spotting | Type | Conference Article | ||
Year | 2014 | Publication | 14th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 476 - 481 | ||
Keywords | Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis | ||||
Abstract | In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries. | ||||
Address | Creete Island; Grecia; September 2014 | ||||
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ISSN | 2167-6445 | ISBN | 978-1-4799-4335-7 | Medium | |
Area | Expedition | Conference | ICFHR | ||
Notes | DAG; 600.056; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FRF2014 | Serial | 2460 | ||
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Author | David Fernandez; Jon Almazan; Nuria Cirera; Alicia Fornes; Josep Llados | ||||
Title | BH2M: the Barcelona Historical Handwritten Marriages database | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 256 - 261 | ||
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Abstract | This paper presents an image database of historical handwritten marriages records stored in the archives of Barcelona cathedral, and the corresponding meta-data addressed to evaluate the performance of document analysis algorithms. The contribution of this paper is twofold. First, it presents a complete ground truth which covers the whole pipeline of handwriting
recognition research, from layout analysis to recognition and understanding. Second, it is the first dataset in the emerging area of genealogical document analysis, where documents are manuscripts pseudo-structured with specific lexicons and the interest is beyond pure transcriptions but context dependent. |
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Address | Creete Island; Grecia; September 2014 | ||||
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ISSN | 1051-4651 | ISBN | Medium | ||
Area | Expedition | Conference | ICPR | ||
Notes | DAG; 600.056; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FAC2014 | Serial | 2461 | ||
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