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| Author | Suman Ghosh; Ernest Valveny | ||||
| Title | R-PHOC: Segmentation-Free Word Spotting using CNN | Type | Conference Article | ||
| Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
Keywords  |
Convolutional neural network; Image segmentation; Artificial neural network; Nearest neighbor search | ||||
| Abstract | arXiv:1707.01294
This paper proposes a region based convolutional neural network for segmentation-free word spotting. Our network takes as input an image and a set of word candidate bound- ing boxes and embeds all bounding boxes into an embedding space, where word spotting can be casted as a simple nearest neighbour search between the query representation and each of the candidate bounding boxes. We make use of PHOC embedding as it has previously achieved significant success in segmentation- based word spotting. Word candidates are generated using a simple procedure based on grouping connected components using some spatial constraints. Experiments show that R-PHOC which operates on images directly can improve the current state-of- the-art in the standard GW dataset and performs as good as PHOCNET in some cases designed for segmentation based word spotting. |
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ GhV2017a | Serial | 3079 | ||
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| Author | Patricia Suarez; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud | ||||
| Title | Near InfraRed Imagery Colorization | Type | Conference Article | ||
| Year | 2018 | Publication | 25th International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 2237 - 2241 | ||
| Keywords |
Convolutional Neural Networks (CNN), Generative Adversarial Network (GAN), Infrared Imagery colorization | ||||
| Abstract | This paper proposes a stacked conditional Generative Adversarial Network-based method for Near InfraRed (NIR) imagery colorization. We propose a variant architecture of Generative Adversarial Network (GAN) that uses multiple
loss functions over a conditional probabilistic generative model. We show that this new architecture/loss-function yields better generalization and representation of the generated colored IR images. The proposed approach is evaluated on a large test dataset and compared to recent state of the art methods using standard metrics. |
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| Address | Athens; Greece; October 2018 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICIP | ||
| Notes | MSIAU; 600.086; 600.130; 600.122 | Approved | no | ||
| Call Number | Admin @ si @ SSV2018b | Serial | 3195 | ||
| Permanent link to this record | |||||
| Author | Patrick Brandao; O. Zisimopoulos; E. Mazomenos; G. Ciutib; Jorge Bernal; M. Visentini-Scarzanell; A. Menciassi; P. Dario; A. Koulaouzidis; A. Arezzo; D.J. Hawkes; D. Stoyanov | ||||
| Title | Towards a computed-aided diagnosis system in colonoscopy: Automatic polyp segmentation using convolution neural networks | Type | Journal | ||
| Year | 2018 | Publication | Journal of Medical Robotics Research | Abbreviated Journal | JMRR |
| Volume | 3 | Issue | 2 | Pages | |
| Keywords |
convolutional neural networks; colonoscopy; computer aided diagnosis | ||||
| Abstract | Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), ne-tune them and study their capabilities for polyp segmentation and detection. We additionally use Shape-from-Shading (SfS) to recover depth and provide a richer representation of the tissue's structure in colonoscopy images. Depth is
incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation IU of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp detection, the top performing models we propose surpass the current state of the art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the rst work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance. |
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | |||
| Notes | MV; no menciona | Approved | no | ||
| Call Number | BZM2018 | Serial | 2976 | ||
| Permanent link to this record | |||||
| Author | Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen | ||||
| Title | Tex-Nets: Binary Patterns Encoded Convolutional Neural Networks for Texture Recognition | Type | Conference Article | ||
| Year | 2017 | Publication | 19th International Conference on Multimodal Interaction | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
Convolutional Neural Networks; Texture Recognition; Local Binary Paterns | ||||
| Abstract | Recognizing materials and textures in realistic imaging conditions is a challenging computer vision problem. For many years, local features based orderless representations were a dominant approach for texture recognition. Recently deep local features, extracted from the intermediate layers of a Convolutional Neural Network (CNN), are used as filter banks. These dense local descriptors from a deep model, when encoded with Fisher Vectors, have shown to provide excellent results for texture recognition. The CNN models, employed in such approaches, take RGB patches as input and train on a large amount of labeled images. We show that CNN models, which we call TEX-Nets, trained using mapped coded images with explicit texture information provide complementary information to the standard deep models trained on RGB patches. We further investigate two deep architectures, namely early and late fusion, to combine the texture and color information. Experiments on benchmark texture datasets clearly demonstrate that TEX-Nets provide complementary information to standard RGB deep network. Our approach provides a large gain of 4.8%, 3.5%, 2.6% and 4.1% respectively in accuracy on the DTD, KTH-TIPS-2a, KTH-TIPS-2b and Texture-10 datasets, compared to the standard RGB network of the same architecture. Further, our final combination leads to consistent improvements over the state-of-the-art on all four datasets. | ||||
| Address | Glasgow; Scothland; November 2017 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ACM | ||
| Notes | LAMP; 600.109; 600.068; 600.120 | Approved | no | ||
| Call Number | Admin @ si @ RKW2017 | Serial | 3038 | ||
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| Author | Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester | ||||
| Title | Anatomical parameterization for volumetric meshing of the liver | Type | Conference Article | ||
| Year | 2014 | Publication | SPIE – Medical Imaging | Abbreviated Journal | |
| Volume | 9036 | Issue | Pages | ||
| Keywords |
Coordinate System; Anatomy Modeling; Parameterization | ||||
| Abstract | A coordinate system describing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specific anatomical landmarks, the coordinate system allows integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric coordinate systems over the surface of anatomical shapes, given their flexibility to set values
at specific locations through boundary conditions. However, most of the existing implementations in medical imaging restrict to either anatomical surfaces, or the depth coordinate with boundary conditions is given at sites of limited geometric diversity. In this paper we present a method for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the volume medial surface. We have applied the methodology to define a common reference system for the liver shape and functional anatomy. This reference system sets a solid base for creating anatomical models of the patient’s liver, and allows comparing livers from several patients in a common framework of reference. |
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| Address | Amsterdam; September 2014 | ||||
| Corporate Author | Thesis | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | SPIE-MI | ||
| Notes | IAM; 600.075 | Approved | no | ||
| Call Number | Admin @ si @ VGG2014 | Serial | 2456 | ||
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| Author | Debora Gil; Aura Hernandez-Sabate; Oriol Rodriguez; J. Mauri; Petia Radeva | ||||
| Title | Statistical Strategy for Anisotropic Adventitia Modelling in IVUS | Type | Journal Article | ||
| Year | 2006 | Publication | IEEE Transactions on Medical Imaging | Abbreviated Journal | |
| Volume | 25 | Issue | 6 | Pages | 768-778 |
| Keywords |
Corners; T-junctions; Wavelets | ||||
| Abstract | Vessel plaque assessment by analysis of intravascular ultrasound sequences is a useful tool for cardiac disease diagnosis and intervention. Manual detection of luminal (inner) and mediaadventitia (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts, and blurred signal response due to ultrasound physical properties trouble automated adventitia segmentation. In order to efficiently approach such a complex problem, we propose blending advanced anisotropic filtering operators and statistical classification techniques into a vessel border modelling strategy. Our systematic statistical analysis shows that the reported adventitia detection achieves an accuracy in the range of interobserver variability regardless of plaque nature, vessel geometry, and incomplete vessel borders. Index Terms–-Anisotropic processing, intravascular ultrasound (IVUS), vessel border segmentation, vessel structure classification. | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | |||
| Notes | IAM;MILAB | Approved | no | ||
| Call Number | IAM @ iam @ GHR2006 | Serial | 1525 | ||
| Permanent link to this record | |||||
| Author | Naveen Onkarappa; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
| Title | Cross-spectral Stereo Correspondence using Dense Flow Fields | Type | Conference Article | ||
| Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 3 | Issue | Pages | 613-617 | |
| Keywords |
Cross-spectral Stereo Correspondence; Dense Optical Flow; Infrared and Visible Spectrum | ||||
| Abstract | This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach. | ||||
| Address | Lisboa; Portugal; January 2014 | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | VISAPP | ||
| Notes | ADAS; 600.055; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ OAV2014 | Serial | 2477 | ||
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| Author | Ariel Amato; Felipe Lumbreras; Angel Sappa | ||||
| Title | A General-purpose Crowdsourcing Platform for Mobile Devices | Type | Conference Article | ||
| Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 3 | Issue | Pages | 211-215 | |
| Keywords |
Crowdsourcing Platform; Mobile Crowdsourcing | ||||
| Abstract | This paper presents details of a general purpose micro-task on-demand platform based on the crowdsourcing philosophy. This platform was specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquity and iii) embedded sensors. The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks. Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and tasksolver). Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way. Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications. Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform. | ||||
| Address | Lisboa; Portugal; January 2014 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | VISAPP | ||
| Notes | ISE; ADAS; 600.054; 600.055; 600.076; 600.078 | Approved | no | ||
| Call Number | Admin @ si @ ALS2014 | Serial | 2478 | ||
| Permanent link to this record | |||||
| Author | Jialuo Chen; Pau Riba; Alicia Fornes; Juan Mas; Josep Llados; Joana Maria Pujadas-Mora | ||||
| Title | Word-Hunter: A Gamesourcing Experience to Validate the Transcription of Historical Manuscripts | Type | Conference Article | ||
| Year | 2018 | Publication | 16th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 528-533 | ||
| Keywords |
Crowdsourcing; Gamification; Handwritten documents; Performance evaluation | ||||
| Abstract | Nowadays, there are still many handwritten historical documents in archives waiting to be transcribed and indexed. Since manual transcription is tedious and time consuming, the automatic transcription seems the path to follow. However, the performance of current handwriting recognition techniques is not perfect, so a manual validation is mandatory. Crowdsourcing is a good strategy for manual validation, however it is a tedious task. In this paper we analyze experiences based in gamification
in order to propose and design a gamesourcing framework that increases the interest of users. Then, we describe and analyze our experience when validating the automatic transcription using the gamesourcing application. Moreover, thanks to the combination of clustering and handwriting recognition techniques, we can speed up the validation while maintaining the performance. |
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| Address | Niagara Falls, USA; August 2018 | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICFHR | ||
| Notes | DAG; 600.097; 603.057; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ CRF2018 | Serial | 3169 | ||
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| Author | Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez | ||||
| Title | Stereo Matching using SGM on the GPU | Type | Report | ||
| Year | 2016 | Publication | Programming and Tuning Massively Parallel Systems | Abbreviated Journal | PUMPS |
| Volume | Issue | Pages | |||
| Keywords |
CUDA; Stereo; Autonomous Vehicle | ||||
| Abstract | Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. | ||||
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| Area | Expedition | Conference | PUMPS | ||
| Notes | ADAS; 600.085; 600.087; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ HCE2016b | Serial | 2776 | ||
| Permanent link to this record | |||||
| Author | Jorge Bernal; David Vazquez (eds) | ||||
| Title | Computer vision Trends and Challenges | Type | Book Whole | ||
| Year | 2013 | Publication | Computer vision Trends and Challenges | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
CVCRD; Computer Vision | ||||
| Abstract | This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.
The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community. We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D. |
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| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | Jorge Bernal; David Vazquez | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940902-2-6 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | ADAS @ adas @ BeV2013 | Serial | 2339 | ||
| Permanent link to this record | |||||
| Author | Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan C. Moure | ||||
| Title | 3D Perception With Slanted Stixels on GPU | Type | Journal Article | ||
| Year | 2021 | Publication | IEEE Transactions on Parallel and Distributed Systems | Abbreviated Journal | TPDS |
| Volume | 32 | Issue | 10 | Pages | 2434-2447 |
| Keywords |
Daniel Hernandez-Juarez; Antonio Espinosa; David Vazquez; Antonio M. Lopez; Juan C. Moure | ||||
| Abstract | This article presents a GPU-accelerated software design of the recently proposed model of Slanted Stixels, which represents the geometric and semantic information of a scene in a compact and accurate way. We reformulate the measurement depth model to reduce the computational complexity of the algorithm, relying on the confidence of the depth estimation and the identification of invalid values to handle outliers. The proposed massively parallel scheme and data layout for the irregular computation pattern that corresponds to a Dynamic Programming paradigm is described and carefully analyzed in performance terms. Performance is shown to scale gracefully on current generation embedded GPUs. We assess the proposed methods in terms of semantic and geometric accuracy as well as run-time performance on three publicly available benchmark datasets. Our approach achieves real-time performance with high accuracy for 2048 × 1024 image sizes and 4 × 4 Stixel resolution on the low-power embedded GPU of an NVIDIA Tegra Xavier. | ||||
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| Notes | ADAS; 600.124; 600.118 | Approved | no | ||
| Call Number | Admin @ si @ HEV2021 | Serial | 3561 | ||
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| Author | Debora Gil; Antonio Esteban Lansaque; Sebastian Stefaniga; Mihail Gaianu; Carles Sanchez | ||||
| Title | Data Augmentation from Sketch | Type | Conference Article | ||
| Year | 2019 | Publication | International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging | Abbreviated Journal | |
| Volume | 11840 | Issue | Pages | 155-162 | |
| Keywords |
Data augmentation; cycleGANs; Multi-objective optimization | ||||
| Abstract | State of the art machine learning methods need huge amounts of data with unambiguous annotations for their training. In the context of medical imaging this is, in general, a very difficult task due to limited access to clinical data, the time required for manual annotations and variability across experts. Simulated data could serve for data augmentation provided that its appearance was comparable to the actual appearance of intra-operative acquisitions. Generative Adversarial Networks (GANs) are a powerful tool for artistic style transfer, but lack a criteria for selecting epochs ensuring also preservation of intra-operative content.
We propose a multi-objective optimization strategy for a selection of cycleGAN epochs ensuring a mapping between virtual images and the intra-operative domain preserving anatomical content. Our approach has been applied to simulate intra-operative bronchoscopic videos and chest CT scans from virtual sketches generated using simple graphical primitives. |
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| Address | Shenzhen; China; October 2019 | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CLIP | ||
| Notes | IAM; 600.145; 601.337; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ GES2019 | Serial | 3359 | ||
| Permanent link to this record | |||||
| Author | Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados | ||||
| Title | A Generic Image Retrieval Method for Date Estimation of Historical Document Collections | Type | Conference Article | ||
| Year | 2022 | Publication | Document Analysis Systems.15th IAPR International Workshop, (DAS2022) | Abbreviated Journal | |
| Volume | 13237 | Issue | Pages | 583–597 | |
| Keywords |
Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG | ||||
| Abstract | Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images. | ||||
| Address | La Rochelle, France; May 22–25, 2022 | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG; 600.140; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ MGR2022 | Serial | 3694 | ||
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| Author | Joost Van de Weijer; Shida Beigpour | ||||
| Title | The Dichromatic Reflection Model: Future Research Directions and Applications | Type | Conference Article | ||
| Year | 2011 | Publication | International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
dblp | ||||
| Abstract | The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability. | ||||
| Address | Algarve, Portugal | ||||
| Corporate Author | Thesis | ||||
| Publisher | SciTePress | Place of Publication | Editor | Mestetskiy, Leonid and Braz, José | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-989-8425-47-8 | Medium | ||
| Area | Expedition | Conference | VISIGRAPP | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ WeB2011 | Serial | 1778 | ||
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