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Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Evaluating Color Representation for Online Road Detection |
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Conference Article |
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2013 |
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ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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594-595 |
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Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations. |
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CVVT:E2M |
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ADAS;ISE |
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Admin @ si @ AGL2013 |
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2794 |
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Author |
Y. Patel; Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas |
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Title |
Dynamic Lexicon Generation for Natural Scene Images |
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Conference Article |
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2016 |
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14th European Conference on Computer Vision Workshops |
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395-410 |
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scene text; photo OCR; scene understanding; lexicon generation; topic modeling; CNN |
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Many scene text understanding methods approach the endtoend recognition problem from a word-spotting perspective and take huge bene t from using small per-image lexicons. Such customized lexicons are normally assumed as given and their source is rarely discussed.
In this paper we propose a method that generates contextualized lexicons
for scene images using only visual information. For this, we exploit
the correlation between visual and textual information in a dataset consisting
of images and textual content associated with them. Using the topic modeling framework to discover a set of latent topics in such a dataset allows us to re-rank a xed dictionary in a way that prioritizes the words that are more likely to appear in a given image. Moreover, we train a CNN that is able to reproduce those word rankings but using only the image raw pixels as input. We demonstrate that the quality of the automatically obtained custom lexicons is superior to a generic frequency-based baseline. |
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Amsterdam; The Netherlands; October 2016 |
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ECCVW |
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DAG; 600.084 |
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Admin @ si @ PGR2016 |
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2825 |
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Author |
Dan Norton; Fernando Vilariño; Onur Ferhat |
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Title |
Memory Field – Creative Engagement in Digital Collections |
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2015 |
Publication |
Internet Librarian International Conference |
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“Memory Fields” is a trans-disciplinary project aiming at the (re)valorisation of digital collections.Its main deliverable is an interface for a dual screen installation, used to access and mix the public library digital collections. The collections being used in this case are a collection of digitised posters from the Spanish Civil War, belonging to the Arxiu General de Catalunya, and a collection of field recordings made by Dan Norton. The system generates visualisations, and the images and sounds are mixed together using narrative primitives of video dj. Users contribute to the digital collections by adding personal memories and observations. The comments and recollections appear as flowers growing in a “memory field” and memories remain public in a Twitter feed (@Memoryfields). |
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London; UK; October 2015 |
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ILI |
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MV;SIAI |
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Admin @ si @NVF2015 |
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2796 |
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Fernando Vilariño; Dimosthenis Karatzas |
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Title |
The Library Living Lab |
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Conference Article |
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2015 |
Publication |
Open Living Lab Days |
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Istanbul; Turkey; August 2015 |
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OLLD |
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MV; DAG;SIAI |
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Admin @ si @ViK2015 |
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2797 |
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Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel |
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Title |
An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres |
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2015 |
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The White Book on Public Library Network from Diputació de Barcelona |
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MV; DAG;SIAI |
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Admin @ si @VKC2015 |
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2798 |
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Author |
Fernando Vilariño |
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Title |
Computer Vision and Performing Arts |
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Conference Article |
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2015 |
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Korean Scholars of Marketing Science |
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Seoul; Korea; October 2015 |
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KAMS |
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MV;SIAI |
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Admin @ si @Vil2015 |
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2799 |
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Author |
Fernando Vilariño; Dan Norton; Onur Ferhat |
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Title |
Memory Fields: DJs in the Library |
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2015 |
Publication |
21 st Symposium of Electronic Arts |
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Vancouver; Canada; August 2015 |
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ISEA |
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;SIAI |
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Admin @ si @VNF2015 |
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2800 |
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Author |
Fernando Vilariño; Dan Norton; Onur Ferhat |
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Title |
The Eye Doesn't Click – Eyetracking and Digital Content Interaction |
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2016 |
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4S/EASST Conference |
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Barcelona; Spain; September 2016 |
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EASST |
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MV; 600.097;SIAI |
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Admin @ si @VNF2016 |
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2801 |
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Author |
Fernando Vilariño |
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Title |
Giving Value to digital collections in the Public Library |
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Conference Article |
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2016 |
Publication |
Librarian 2020 |
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Brussels; Belgium; October 2016 |
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LIB |
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MV; 600.097;SIAI |
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Admin @ si @Vil2016a |
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2802 |
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Fernando Vilariño; Dimosthenis Karatzas |
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A Living Lab approach for Citizen Science in Libraries |
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2016 |
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1st International ECSA Conference |
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Berlin; Germany; May 2016 |
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ECSA |
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MV; DAG; 600.084; 600.097;SIAI |
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Admin @ si @ViK2016 |
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2804 |
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Author |
Fernando Vilariño |
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Dissemination, creation and education from archives: Case study of the collection of Digitized Visual Poems from Joan Brossa Foundation |
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2016 |
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International Workshop on Poetry: Archives, Poetries and Receptions |
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Barcelona; Spain; October 2016 |
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POETRY |
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MV; 600.097;SIAI |
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Admin @ si @Vil2016b |
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2805 |
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Author |
Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira |
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Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives |
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2016 |
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Robotics and Autonomous Systems |
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RAS |
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83 |
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312-325 |
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Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives |
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When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques. |
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Elsevier B.V. |
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ADAS; 600.086, 600.076 |
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Admin @ si @OSS2016a |
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2806 |
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Angel Sappa; P. Carvajal; Cristhian A. Aguilera-Carrasco; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla |
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Wavelet based visible and infrared image fusion: a comparative study |
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2016 |
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Sensors |
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SENS |
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16 |
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6 |
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1-15 |
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Image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform |
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This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR). |
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ADAS; 600.086; 600.076 |
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Admin @ si @SCA2016 |
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2807 |
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Cristhian A. Aguilera-Carrasco; F. Aguilera; Angel Sappa; C. Aguilera; Ricardo Toledo |
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Learning cross-spectral similarity measures with deep convolutional neural networks |
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2016 |
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29th IEEE Conference on Computer Vision and Pattern Recognition Worshops |
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The simultaneous use of images from different spectracan be helpful to improve the performance of many computer vision tasks. The core idea behind the usage of crossspectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN architectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Experimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Additionally, our experiments show that some CNN architectures are capable of generalizing between different crossspectral domains. |
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Las vegas; USA; June 2016 |
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CVPRW |
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ADAS; 600.086; 600.076 |
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Admin @ si @AAS2016 |
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2809 |
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Angel Sappa; Cristhian A. Aguilera-Carrasco; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo |
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Monocular visual odometry: A cross-spectral image fusion based approach |
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2016 |
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Robotics and Autonomous Systems |
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RAS |
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85 |
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26-36 |
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Monocular visual odometry; LWIR-RGB cross-spectral imaging; Image fusion |
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This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is empirically obtained by means of a mutual information based evaluation metric. The objective is to have a flexible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odometry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. |
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Publisher |
Elsevier B.V. |
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Notes |
ADAS;600.086; 600.076 |
Approved |
no |
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Call Number |
Admin @ si @SAC2016 |
Serial |
2811 |
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