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Author |
Hugo Berti; Angel Sappa; Osvaldo Agamennoni |
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Title |
Autonomous robot navigation with a global and asymptotic convergence |
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Conference Article |
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Year |
2007 |
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IEEE International Conference on Robotics and Automation |
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2712–2717 |
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Roma (Italy) |
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ICRA |
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ADAS |
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ADAS @ adas @ BSA2007 |
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796 |
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Author |
Hugo Berti; Angel Sappa; Osvaldo Agamennoni |
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Title |
Improved Dynamic Window Approach by Using Lyapunov Stability Criteria |
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Journal |
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Year |
2008 |
Publication |
Latin American Applied Research |
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38 |
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4 |
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289–298 |
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ADAS |
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no |
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ADAS @ adas @ BSA2008 |
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1056 |
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Author |
Enrique Cabello; Cristina Conde; Angel Serrano; Licesio Rodriguez; David Vazquez |
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Title |
Empleo de sistemas biométricos para el reconocimiento de personas en aeropuertos |
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Journal Article |
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Year |
2006 |
Publication |
Instituto Universitario de Investigación sobre Seguridad Interior (IUSI 2006) |
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Surveillance; Face detection; Face recognition |
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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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invisible;ADAS |
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no |
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ADAS @ adas @ CCS2006a |
Serial |
1672 |
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Author |
Diego Alejandro Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Camera Egomotion Estimation in the ADAS Context |
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Conference Article |
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Year |
2010 |
Publication |
13th International IEEE Annual Conference on Intelligent Transportation Systems |
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Pages |
1415–1420 |
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Abstract |
Camera-based Advanced Driver Assistance Systems (ADAS) have concentrated many research efforts in the last decades. Proposals based on monocular cameras require the knowledge of the camera pose with respect to the environment, in order to reach an efficient and robust performance. A common assumption in such systems is considering the road as planar, and the camera pose with respect to it as approximately known. However, in real situations, the camera pose varies along time due to the vehicle movement, the road slope, and irregularities on the road surface. Thus, the changes in the camera position and orientation (i.e., the egomotion) are critical information that must be estimated at every frame to avoid poor performances. This work focuses on egomotion estimation from a monocular camera under the ADAS context. We review and compare egomotion methods with simulated and real ADAS-like sequences. Basing on the results of our experiments, we show which of the considered nonlinear and linear algorithms have the best performance in this domain. |
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Madeira Island (Portugal) |
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2153-0009 |
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978-1-4244-7657-2 |
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ITSC |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ CPL2010 |
Serial |
1425 |
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Author |
Victor Campmany; Sergio Silva; Antonio Espinosa; Juan Carlos Moure; David Vazquez; Antonio Lopez |
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Title |
GPU-based pedestrian detection for autonomous driving |
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Conference Article |
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Year |
2016 |
Publication |
16th International Conference on Computational Science |
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Volume |
80 |
Issue |
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Pages |
2377-2381 |
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Keywords |
Pedestrian detection; Autonomous Driving; CUDA |
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Abstract |
We propose a real-time pedestrian detection system for the embedded Nvidia Tegra X1 GPU-CPU hybrid platform. The pipeline is composed by the following state-of-the-art algorithms: Histogram of Local Binary Patterns (LBP) and Histograms of Oriented Gradients (HOG) features extracted from the input image; Pyramidal Sliding Window technique for foreground segmentation; and Support Vector Machine (SVM) for classification. Results show a 8x speedup in the target Tegra X1 platform and a better performance/watt ratio than desktop CUDA platforms in study. |
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San Diego; CA; USA; June 2016 |
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ICCS |
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Notes |
ADAS; 600.085; 600.082; 600.076 |
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no |
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Call Number |
ADAS @ adas @ CSE2016 |
Serial |
2741 |
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Author |
Victor Campmany; Sergio Silva; Juan Carlos Moure; Antoni Espinosa; David Vazquez; Antonio Lopez |
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Title |
GPU-based pedestrian detection for autonomous driving |
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Abstract |
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Year |
2015 |
Publication |
Programming and Tunning Massive Parallel Systems |
Abbreviated Journal |
PUMPS |
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Keywords |
Autonomous Driving; ADAS; CUDA; Pedestrian Detection |
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Abstract |
Pedestrian detection for autonomous driving has gained a lot of prominence during the last few years. Besides the fact that it is one of the hardest tasks within computer vision, it involves huge computational costs. The real-time constraints in the field are tight, and regular processors are not able to handle the workload obtaining an acceptable ratio of frames per second (fps). Moreover, multiple cameras are required to obtain accurate results, so the need to speed up the process is even higher. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system. Further, we introduce significant algorithmic adjustments and optimizations to adapt the problem to the GPU architecture. The aim is to provide a system capable of running in real-time obtaining reliable results. |
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Barcelona; Spain |
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PUMPS |
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PUMPS |
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ADAS; 600.076; 600.082; 600.085 |
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no |
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Call Number |
ADAS @ adas @ CSM2015 |
Serial |
2644 |
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Author |
Victor Campmany; Sergio Silva; Juan Carlos Moure; Toni Espinosa; David Vazquez; Antonio Lopez |
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Title |
GPU-based pedestrian detection for autonomous driving |
Type |
Conference Article |
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Year |
2016 |
Publication |
GPU Technology Conference |
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Keywords |
Pedestrian Detection; GPU |
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Abstract |
Pedestrian detection for autonomous driving is one of the hardest tasks within computer vision, and involves huge computational costs. Obtaining acceptable real-time performance, measured in frames per second (fps), for the most advanced algorithms is nowadays a hard challenge. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system that includes LBP and HOG as feature descriptors and SVM and Random forest as classifiers. We introduce significant algorithmic adjustments and optimizations to adapt the problem to the NVIDIA GPU architecture. The aim is to deploy a real-time system providing reliable results. |
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Silicon Valley; San Francisco; USA; April 2016 |
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GTC |
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ADAS; 600.085; 600.082; 600.076 |
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no |
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Call Number |
ADAS @ adas @ CSM2016 |
Serial |
2737 |
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Author |
Ferran Diego; Jose Manuel Alvarez; Joan Serrat; Antonio Lopez |
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Title |
Vision-based road detection via on-line video registration |
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Conference Article |
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Year |
2010 |
Publication |
13th Annual International Conference on Intelligent Transportation Systems |
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Pages |
1135–1140 |
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Keywords |
video alignment; road detection |
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Abstract |
TB6.2
Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. Significant efforts have been made in order to solve this task using vision-based techniques. The major challenge is to deal with lighting variations and the presence of objects on the road surface. In this paper, we propose a new road detection method to infer the areas of the image depicting road surfaces without performing any image segmentation. The idea is to previously segment manually or semi-automatically the road region in a traffic-free reference video record on a first drive. And then to transfer these regions to the frames of a second video sequence acquired later in a second drive through the same road, in an on-line manner. This is possible because we are able to automatically align the two videos in time and space, that is, to synchronize them and warp each frame of the first video to its corresponding frame in the second one. The geometric transform can thus transfer the road region to the present frame on-line. In order to reduce the different lighting conditions which are present in outdoor scenarios, our approach incorporates a shadowless feature space which represents an image in an illuminant-invariant feature space. Furthermore, we propose a dynamic background subtraction algorithm which removes the regions containing vehicles in the observed frames which are within the transferred road region. |
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Madeira Island (Portugal) |
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2153-0009 |
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978-1-4244-7657-2 |
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ITSC |
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ADAS |
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Call Number |
ADAS @ adas @ DAS2010 |
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1424 |
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Author |
Daniel Ponsa; Jordi Vitria |
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Title |
Mobile monitoring system using an agent-oriented approach |
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Miscellaneous |
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Year |
1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes |
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Bilbao |
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ADAS;OR;MV |
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ADAS @ adas @ DaV1999 |
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21 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
SFM for Planar Scenes: a Direct and Robust Approach |
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Miscellaneous |
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2005 |
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International Conference on Informatics in Control, Automation and Robotics (ICINCO 2005) |
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Barcelona (Spain) |
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ADAS |
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ADAS @ adas @ DoS2005a |
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559 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Appearance-based 3D Face Tracker: An Evaluation Study |
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Miscellaneous |
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2005 |
Publication |
2nd IEEE Int. Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, 121–128 |
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Beijing (China) |
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ADAS |
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ADAS @ adas @ DoS2005b |
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580 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data |
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Miscellaneous |
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2006 |
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International Conference on Computer Vision Theory and Applications, (2): 310–317 |
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ADAS @ adas @ DoS2006a |
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636 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
3D Motion from Image Derivatives using the Least Trimmed Square Regression |
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Book Chapter |
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2006 |
Publication |
International Workshop on Intelligent Computing in Pattern Analysis/Synthesis (IWICPAS´06), LNCS 4153: 76–84 |
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Xi'an (China) |
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ADAS |
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ADAS @ adas @ DoS2006b |
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690 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Rigid and Non-Rigid Face Motion Tracking by Aligning Texture Maps and Stereo-Based 3D Models |
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Book Chapter |
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2006 |
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8th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS´06), LNCS 4179: 675–684 |
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Antwerp (Belgium) |
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ADAS |
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ADAS @ adas @ DoS2006c |
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689 |
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Fadi Dornaika; Angel Sappa |
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Title |
3D Face Tracking using Appearance Registration and Robust Iterative Closest Point Algorithm |
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Book Chapter |
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2006 |
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21st International Symposium on Computer and Information Sciences (ISCIS´06), LNCS 4263: 532–541 |
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Istanbul (Turkey) |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ DoS2006d |
Serial |
688 |
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