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Author | Carles Sanchez; Antonio Esteban Lansaque; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil | ||||
Title | Towards a Videobronchoscopy Localization System from Airway Centre Tracking | Type | Conference Article | ||
Year | 2017 | Publication | 12th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | Issue | Pages | 352-359 | ||
Keywords | Video-bronchoscopy; Lung cancer diagnosis; Airway lumen detection; Region tracking; Guided bronchoscopy navigation | ||||
Abstract | Bronchoscopists use fluoroscopy to guide flexible bronchoscopy to the lesion to be biopsied without any kind of incision. Being fluoroscopy an imaging technique based on X-rays, the risk of developmental problems and cancer is increased in those subjects exposed to its application, so minimizing radiation is crucial. Alternative guiding systems such as electromagnetic navigation require specific equipment, increase the cost of the clinical procedure and still require fluoroscopy. In this paper we propose an image based guiding system based on the extraction of airway centres from intra-operative videos. Such anatomical landmarks are matched to the airway centreline extracted from a pre-planned CT to indicate the best path to the nodule. We present a
feasibility study of our navigation system using simulated bronchoscopic videos and a multi-expert validation of landmarks extraction in 3 intra-operative ultrathin explorations. |
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Address | Porto; Portugal; February 2017 | ||||
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Area | Expedition | Conference | VISAPP | ||
Notes | IAM; 600.096; 600.075; 600.145 | Approved | no | ||
Call Number | Admin @ si @ SEB2017 | Serial | 2943 | ||
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Author | Joan Serrat; Ferran Diego; Felipe Lumbreras; Jose Manuel Alvarez; Antonio Lopez; C. Elvira | ||||
Title | Dynamic Comparison of Headlights | Type | Journal Article | ||
Year | 2008 | Publication | Journal of Automobile Engineering | Abbreviated Journal | |
Volume | 222 | Issue | 5 | Pages | 643–656 |
Keywords | video alignment | ||||
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ SDL2008a | Serial | 958 | ||
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Author | Oscar Argudo; Marc Comino; Antonio Chica; Carlos Andujar; Felipe Lumbreras | ||||
Title | Segmentation of aerial images for plausible detail synthesis | Type | Journal Article | ||
Year | 2018 | Publication | Computers & Graphics | Abbreviated Journal | CG |
Volume | 71 | Issue | Pages | 23-34 | |
Keywords | Terrain editing; Detail synthesis; Vegetation synthesis; Terrain rendering; Image segmentation | ||||
Abstract | The visual enrichment of digital terrain models with plausible synthetic detail requires the segmentation of aerial images into a suitable collection of categories. In this paper we present a complete pipeline for segmenting high-resolution aerial images into a user-defined set of categories distinguishing e.g. terrain, sand, snow, water, and different types of vegetation. This segmentation-for-synthesis problem implies that per-pixel categories must be established according to the algorithms chosen for rendering the synthetic detail. This precludes the definition of a universal set of labels and hinders the construction of large training sets. Since artists might choose to add new categories on the fly, the whole pipeline must be robust against unbalanced datasets, and fast on both training and inference. Under these constraints, we analyze the contribution of common per-pixel descriptors, and compare the performance of state-of-the-art supervised learning algorithms. We report the findings of two user studies. The first one was conducted to analyze human accuracy when manually labeling aerial images. The second user study compares detailed terrains built using different segmentation strategies, including official land cover maps. These studies demonstrate that our approach can be used to turn digital elevation models into fully-featured, detailed terrains with minimal authoring efforts. | ||||
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ISSN | 0097-8493 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | MSIAU; 600.086; 600.118 | Approved | no | ||
Call Number | Admin @ si @ ACC2018 | Serial | 3147 | ||
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Author | Cesar Isaza; Joaquin Salas; Bogdan Raducanu | ||||
Title | Rendering ground truth data sets to detect shadows cast by static objects in outdoors | Type | Journal Article | ||
Year | 2014 | Publication | Multimedia Tools and Applications | Abbreviated Journal | MTAP |
Volume | 70 | Issue | 1 | Pages | 557-571 |
Keywords | Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection | ||||
Abstract | In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically. | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1380-7501 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ ISR2014 | Serial | 2229 | ||
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Author | Enrique Cabello; Cristina Conde; Angel Serrano; Licesio Rodriguez; David Vazquez | ||||
Title | Empleo de sistemas biométricos para el reconocimiento de personas en aeropuertos | Type | Miscellaneous | ||
Year | 2006 | Publication | Instituto Universitario de Investigación sobre Seguridad Interior (IUSI 2006) | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Surveillance; Face detection; Face recognition | ||||
Abstract | El presente proyecto se desarrolló a lo largo del año 2005, probando un prototipo de un sistema de verificación facial con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. Se diseñaron varios experimentos, agrupados en dos clases. En el primer tipo, el sistema es entrenado con imágenes obtenidas en condiciones de laboratorio y luego probado con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. En el segundo caso, tanto las imágenes de entrenamiento como las de prueba corresponden a imágenes extraídas de Barajas. Se ha desarrollado un sistema completo, que incluye adquisición y digitalización de las imágenes, localización y recorte de las caras en escena, verificación de sujetos y obtención de resultados. Los resultados muestran, que, en general, un sistema de verificación facial basado en imágenes puede ser una ayuda a un operario que deba estar vigilando amplias zonas. | ||||
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Notes | invisible;ADAS | Approved | no | ||
Call Number | ADAS @ adas @ CCS2006a | Serial | 1672 | ||
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Author | Gemma Sanchez; Josep Llados; Enric Marti | ||||
Title | Segmentation and analysis of linial texture in plans | Type | Conference Article | ||
Year | 1997 | Publication | Actes de la conférence Artificielle et Complexité. | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Structural Texture, Voronoi, Hierarchical Clustering, String Matching. | ||||
Abstract | The problem of texture segmentation and interpretation is one of the main concerns in the field of document analysis. Graphical documents often contain areas characterized by a structural texture whose recognition allows both the document understanding, and its storage in a more compact way. In this work, we focus on structural linial textures of regular repetition contained in plan documents. Starting from an atributed graph which represents the vectorized input image, we develop a method to segment textured areas and recognize their placement rules. We wish to emphasize that the searched textures do not follow a predefined pattern. Minimal closed loops of the input graph are computed, and then hierarchically clustered. In this hierarchical clustering, a distance function between two closed loops is defined in terms of their areas difference and boundary resemblance computed by a string matching procedure. Finally it is noted that, when the texture consists of isolated primitive elements, the same method can be used after computing a Voronoi Tesselation of the input graph. | ||||
Address | Paris, France | ||||
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Publisher | Place of Publication | Paris | Editor | ||
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Area | Expedition | Conference | AERFAI | ||
Notes | DAG;IAM; | Approved | no | ||
Call Number | IAM @ iam @ SLM1997 | Serial | 1649 | ||
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Author | Jose Manuel Alvarez; Antonio Lopez | ||||
Title | Road Detection Based on Illuminant Invariance | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
Volume | 12 | Issue | 1 | Pages | 184-193 |
Keywords | road detection | ||||
Abstract | By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms. | ||||
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ AlL2011 | Serial | 1456 | ||
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Author | Xinhang Song; Luis Herranz; Shuqiang Jiang | ||||
Title | Depth CNNs for RGB-D Scene Recognition: Learning from Scratch Better than Transferring from RGB-CNNs | Type | Conference Article | ||
Year | 2017 | Publication | 31st AAAI Conference on Artificial Intelligence | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | RGB-D scene recognition; weakly supervised; fine tune; CNN | ||||
Abstract | Scene recognition with RGB images has been extensively studied and has reached very remarkable recognition levels, thanks to convolutional neural networks (CNN) and large scene datasets. In contrast, current RGB-D scene data is much more limited, so often leverages RGB large datasets, by transferring pretrained RGB CNN models and fine-tuning with the target RGB-D dataset. However, we show that this approach has the limitation of hardly reaching bottom layers, which is key to learn modality-specific features. In contrast, we focus on the bottom layers, and propose an alternative strategy to learn depth features combining local weakly supervised training from patches followed by global fine tuning with images. This strategy is capable of learning very discriminative depth-specific features with limited depth images, without resorting to Places-CNN. In addition we propose a modified CNN architecture to further match the complexity of the model and the amount of data available. For RGB-D scene recognition, depth and RGB features are combined by projecting them in a common space and further leaning a multilayer classifier, which is jointly optimized in an end-to-end network. Our framework achieves state-of-the-art accuracy on NYU2 and SUN RGB-D in both depth only and combined RGB-D data. | ||||
Address | San Francisco CA; February 2017 | ||||
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Area | Expedition | Conference | AAAI | ||
Notes | LAMP; 600.120 | Approved | no | ||
Call Number | Admin @ si @ SHJ2017 | Serial | 2967 | ||
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Author | Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Gloria Fernandez Esparrach; Xavier Gray; Olivier Romain; F. Javier Sanchez; Aymeric Histace | ||||
Title | Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis | Type | Conference Article | ||
Year | 2017 | Publication | 4th International Workshop on Computer Assisted and Robotic Endoscopy | Abbreviated Journal | |
Volume | Issue | Pages | 29-41 | ||
Keywords | Polyp detection; colonoscopy; real time; spatio temporal coherence | ||||
Abstract | Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been proposed but none of them are used in the clinical room mainly due to computational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability module and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detection method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our adaptation strategy. |
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Address | Quebec; Canada; September 2017 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CARE | ||
Notes | MV; 600.096; 600.075 | Approved | no | ||
Call Number | Admin @ si @ ABS2017b | Serial | 2977 | ||
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Author | Adria Rico; Alicia Fornes | ||||
Title | Camera-based Optical Music Recognition using a Convolutional Neural Network | Type | Conference Article | ||
Year | 2017 | Publication | 12th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 27-28 | ||
Keywords | optical music recognition; document analysis; convolutional neural network; deep learning | ||||
Abstract | Optical Music Recognition (OMR) consists in recognizing images of music scores. Contrary to expectation, the current OMR systems usually fail when recognizing images of scores captured by digital cameras and smartphones. In this work, we propose a camera-based OMR system based on Convolutional Neural Networks, showing promising preliminary results | ||||
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Area | Expedition | Conference | GREC | ||
Notes | DAG;600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RiF2017 | Serial | 3059 | ||
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Author | Cristhian Aguilera; Xavier Soria; Angel Sappa; Ricardo Toledo | ||||
Title | RGBN Multispectral Images: a Novel Color Restoration Approach | Type | Conference Article | ||
Year | 2017 | Publication | 15th International Conference on Practical Applications of Agents and Multi-Agent System | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Multispectral Imaging; Free Sensor Model; Neural Network | ||||
Abstract | This paper describes a color restoration technique used to remove NIR information from single sensor cameras where color and near-infrared images are simultaneously acquired|referred to in the literature as RGBN images. The proposed approach is based on a neural network architecture that learns the NIR information contained in the RGBN images. The proposed approach is evaluated on real images obtained by using a pair of RGBN cameras. Additionally, qualitative comparisons with a nave color correction technique based on mean square
error minimization are provided. |
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Address | Porto; Portugal; June 2017 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | PAAMS | ||
Notes | ADAS; MSIAU; 600.118; 600.122 | Approved | no | ||
Call Number | Admin @ si @ ASS2017 | Serial | 2918 | ||
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Author | Maria Elena Meza-de-Luna; Juan Ramon Terven Salinas; Bogdan Raducanu; Joaquin Salas | ||||
Title | Assessing the Influence of Mirroring on the Perception of Professional Competence using Wearable Technology | Type | Journal Article | ||
Year | 2016 | Publication | IEEE Transactions on Affective Computing | Abbreviated Journal | TAC |
Volume | 9 | Issue | 2 | Pages | 161-175 |
Keywords | Mirroring; Nodding; Competence; Perception; Wearable Technology | ||||
Abstract | Nonverbal communication is an intrinsic part in daily face-to-face meetings. A frequently observed behavior during social interactions is mirroring, in which one person tends to mimic the attitude of the counterpart. This paper shows that a computer vision system could be used to predict the perception of competence in dyadic interactions through the automatic detection of mirroring
events. To prove our hypothesis, we developed: (1) A social assistant for mirroring detection, using a wearable device which includes a video camera and (2) an automatic classifier for the perception of competence, using the number of nodding gestures and mirroring events as predictors. For our study, we used a mixed-method approach in an experimental design where 48 participants acting as customers interacted with a confederated psychologist. We found that the number of nods or mirroring events has a significant influence on the perception of competence. Our results suggest that: (1) Customer mirroring is a better predictor than psychologist mirroring; (2) the number of psychologist’s nods is a better predictor than the number of customer’s nods; (3) except for the psychologist mirroring, the computer vision algorithm we used worked about equally well whether it was acquiring images from wearable smartglasses or fixed cameras. |
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Area | Expedition | Conference | |||
Notes | LAMP; 600.072; | Approved | no | ||
Call Number | Admin @ si @ MTR2016 | Serial | 2826 | ||
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Author | Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; I. Bardaji; Horst Bunke | ||||
Title | A Generic Framework for Median Graph Computation based on a Recursive Embedding Approach | Type | Journal Article | ||
Year | 2011 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 115 | Issue | 7 | Pages | 919-928 |
Keywords | Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition | ||||
Abstract | The median graph has been shown to be a good choice to obtain a represen- tative of a set of graphs. However, its computation is a complex problem. Recently, graph embedding into vector spaces has been proposed to obtain approximations of the median graph. The problem with such an approach is how to go from a point in the vector space back to a graph in the graph space. The main contribution of this paper is the generalization of this previ- ous method, proposing a generic recursive procedure that permits to recover the graph corresponding to a point in the vector space, introducing only the amount of approximation inherent to the use of graph matching algorithms. In order to evaluate the proposed method, we compare it with the set me- dian and with the other state-of-the-art embedding-based methods for the median graph computation. The experiments are carried out using four dif- ferent databases (one semi-artificial and three containing real-world data). Results show that with the proposed approach we can obtain better medi- ans, in terms of the sum of distances to the training graphs, than with the previous existing methods. | ||||
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Notes | DAG | Approved | no | ||
Call Number | IAM @ iam @ FKV2011 | Serial | 1831 | ||
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Author | Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas | ||||
Title | Head-gestures mirroring detection in dyadic social linteractions with computer vision-based wearable devices | Type | Journal Article | ||
Year | 2016 | Publication | Neurocomputing | Abbreviated Journal | NEUCOM |
Volume | 175 | Issue | B | Pages | 866–876 |
Keywords | Head gestures recognition; Mirroring detection; Dyadic social interaction analysis; Wearable devices | ||||
Abstract | During face-to-face human interaction, nonverbal communication plays a fundamental role. A relevant aspect that takes part during social interactions is represented by mirroring, in which a person tends to mimic the non-verbal behavior (head and body gestures, vocal prosody, etc.) of the counterpart. In this paper, we introduce a computer vision-based system to detect mirroring in dyadic social interactions with the use of a wearable platform. In our context, mirroring is inferred as simultaneous head noddings displayed by the interlocutors. Our approach consists of the following steps: (1) facial features extraction; (2) facial features stabilization; (3) head nodding recognition; and (4) mirroring detection. Our system achieves a mirroring detection accuracy of 72% on a custom mirroring dataset. | ||||
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Notes | LAMP; 600.072; 600.068; | Approved | no | ||
Call Number | Admin @ si @ TRM2016 | Serial | 2721 | ||
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Author | Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez | ||||
Title | Information Extraction in Handwritten Marriage Licenses Books Using the MGGI Methodology | Type | Conference Article | ||
Year | 2017 | Publication | 8th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 10255 | Issue | Pages | 287-294 | |
Keywords | Handwritten Text Recognition; Information extraction; Language modeling; MGGI; Categories-based language model | ||||
Abstract | Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demographic and genealogical research. For example, marriage license books have been used for centuries by ecclesiastical and secular institutions to register marriages. These books follow a simple structure of the text in the records with a evolutionary vocabulary, mainly composed of proper names that change along the time. This distinct vocabulary makes automatic transcription and semantic information extraction difficult tasks. In previous works we studied the use of category-based language models and how a Grammatical Inference technique known as MGGI could improve the accuracy of these tasks. In this work we analyze the main causes of the semantic errors observed in previous results and apply a better implementation of the MGGI technique to solve these problems. Using the resulting language model, transcription and information extraction experiments have been carried out, and the results support our proposed approach. | ||||
Address | Faro; Portugal; June 2017 | ||||
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Publisher | Place of Publication | Editor | L.A. Alexandre; J.Salvador Sanchez; Joao M. F. Rodriguez | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-3-319-58837-7 | Medium | ||
Area | Expedition | Conference | IbPRIA | ||
Notes | DAG; 602.006; 600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RFV2017 | Serial | 2952 | ||
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