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Author |
Xavier Baro |
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Title |
Probabilistic Darwin Machines: A New Approach to Develop Evolutionary Object Detection |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Ever since computers were invented, we have wondered whether they might perform some of the human quotidian tasks. One of the most studied and still nowadays less understood problem is the capacity to learn from our experiences and how we generalize the knowledge that we acquire. One of that unaware tasks for the persons and that more interest is awakening in different scientific areas since the beginning, is the one that is known as pattern recognition. The creation of models that represent the world that surrounds us, help us for recognizing objects in our environment, to predict situations, to identify behaviors... All this information allows us to adapt ourselves and to interact with our environment. The capacity of adaptation of individuals to their environment has been related to the amount of patterns that are capable of identifying.
This thesis faces the pattern recognition problem from a Computer Vision point of view, taking one of the most paradigmatic and extended approaches to object detection as starting point. After studying this approach, two weak points are identified: The first makes reference to the description of the objects, and the second is a limitation of the learning algorithm, which hampers the utilization of best descriptors.
In order to address the learning limitations, we introduce evolutionary computation techniques to the classical object detection approach.
After testing the classical evolutionary approaches, such as genetic algorithms, we develop a new learning algorithm based on Probabilistic Darwin Machines, which better adapts to the learning problem. Once the learning limitation is avoided, we introduce a new feature set, which maintains the benefits of the classical feature set, adding the ability to describe non localities. This combination of evolutionary learning algorithm and features is tested on different public data sets, outperforming the results obtained by the classical approach. |
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Barcelona (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Jordi Vitria |
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OR;HuPBA;MV |
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BCNPCL @ bcnpcl @ Bar2009 |
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1262 |
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Author |
David Rotger |
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Title |
Analysis and Multi-Modal Fusion of coronary Images |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The framework of this thesis is to study in detail different techniques and tools for medical image registration in order to ease the daily life of clinical experts in cardiology. The first aim of this thesis is providing computer tools for
fusing IVUS and angiogram data is of high clinical interest to help the physicians locate in IVUS data and decide which lesion is observed, how long it is, how far from a bifurcation or another lesions stays, etc. This thesis proves and
validates that we can segment the catheter path in angiographies using geodesic snakes (based on fast marching algorithm), a three-dimensional reconstruction of the catheter inspired in stereo vision and a new technique to fuse IVUS
and angiograms that establishes exact correspondences between them. We have developed a new workstation called iFusion that has four strong advantages: registration of IVUS and angiographic images with sub-pixel precision, it works on- and off-line, it is independent on the X-ray system and there is no need of daily calibration. The second aim of the thesis is devoted to developing a computer-aided analysis of IVUS for image-guided intervention. We have designed, implemented
and validated a robust algorithm for stent extraction and reconstruction from IVUS videos. We consider a very special and recent kind of stents, bioabsorbable stents that represent a great clinical challenge due to their property to be
absorbed by time and thus avoiding the “danger” of neostenosis as one of the main problems of metallic stents. We present a new and very promising algorithm based on an optimized cascade of multiple classifiers to automatically detect individual stent struts of a very novel bioabsorbable drug eluting coronary stent. This problem represents a very challenging target given the variability in contrast, shape and grey levels of the regions to be detected, what is
denoted by the high variability between the specialists (inter-observer variability of 0.14~$\pm$0.12). The obtained results of the automatic strut detection are within the inter-observer variability. |
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Barcelona (Espanya) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Petia Radeva |
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Admin @ si @ Rot2009 |
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1261 |
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Author |
Pau Baiget |
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Title |
Modeling Human Behavior for Image Sequence Understanding and Generation |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The comprehension of animal behavior, especially human behavior, is one of the most ancient and studied problems since the beginning of civilization. The big list of factors that interact to determine a person action require the collaboration of different disciplines, such as psichology, biology, or sociology. In the last years the analysis of human behavior has received great attention also from the computer vision community, given the latest advances in the acquisition of human motion data from image sequences.
Despite the increasing availability of that data, there still exists a gap towards obtaining a conceptual representation of the obtained observations. Human behavior analysis is based on a qualitative interpretation of the results, and therefore the assignment of concepts to quantitative data is linked to a certain ambiguity.
This Thesis tackles the problem of obtaining a proper representation of human behavior in the contexts of computer vision and animation. On the one hand, a good behavior model should permit the recognition and explanation the observed activity in image sequences. On the other hand, such a model must allow the generation of new synthetic instances, which model the behavior of virtual agents.
First, we propose methods to automatically learn the models from observations. Given a set of quantitative results output by a vision system, a normal behavior model is learnt. This results provides a tool to determine the normality or abnormality of future observations. However, machine learning methods are unable to provide a richer description of the observations. We confront this problem by means of a new method that incorporates prior knowledge about the enviornment and about the expected behaviors. This framework, formed by the reasoning engine FMTL and the modeling tool SGT allows the generation of conceptual descriptions of activity in new image sequences. Finally, we demonstrate the suitability of the proposed framework to simulate behavior of virtual agents, which are introduced into real image sequences and interact with observed real agents, thereby easing the generation of augmented reality sequences.
The set of approaches presented in this Thesis has a growing set of potential applications. The analysis and description of behavior in image sequences has its principal application in the domain of smart video--surveillance, in order to detect suspicious or dangerous behaviors. Other applications include automatic sport commentaries, elderly monitoring, road traffic analysis, and the development of semantic video search engines. Alternatively, behavioral virtual agents allow to simulate accurate real situations, such as fires or crowds. Moreover, the inclusion of virtual agents into real image sequences has been widely deployed in the games and cinema industries. |
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Bellaterra (Spain) |
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Thesis |
Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Jordi Gonzalez;Xavier Roca |
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Admin @ si @ Bai2009 |
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1210 |
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Author |
Robert Benavente; Laura Igual; Fernando Vilariño |
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Title |
Current Challenges in Computer Vision |
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2008 |
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Proccedings of the Third Internal Workshop |
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978-84-936529-0-6 |
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CVCRD |
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MILAB;CIC;SIAI |
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no |
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Call Number |
BCNPCL @ bcnpcl @ BIV2008 |
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1110 |
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Author |
Robert Benavente |
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Title |
A Parametric Model for Computational Colour Naming |
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2007 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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PhD Thesis |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Maria Vanrell |
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CIC |
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CAT @ cat @ Ben2007 |
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1108 |
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Author |
Daniel Ponsa |
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Title |
Model-Based Visual Localisation of Contours and Vehicles |
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2007 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Phd Thesis |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Antonio Lopez;Xavier Roca |
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978-84-935251-3-2 |
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ADAS @ adas @ Pon2007 |
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1107 |
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Author |
Miquel Ferrer |
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Title |
Theory and Algorithms on the Median Graph. Application to Graph-based Classification and Clustering |
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2008 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Ph.D. thesis |
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Francesc Serratosa Casanelles;Ernest Valveny |
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978-84-935251-7-0 |
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Admin @ si @ Fer2008 |
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1105 |
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Author |
Alfons Juan-Ciscar; Gemma Sanchez |
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Title |
PRIS 2008. Pattern Recognition in Information Systems. Proceedings of the 8th international Workshop on Pattern Recognition in Information systems – PRIS 2008, in conjunction with ICEIS 2008 |
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2008 |
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Barcelona (Spain) |
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DAG |
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DAG @ dag @ JuS2008 |
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1054 |
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Author |
Liu Wenyin; Josep Llados; Jean-Marc Ogier |
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Title |
Graphics Recognition. Recent Advances and New Opportunities. |
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2008 |
Publication |
7th International Workshop, Selected Papers, |
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5046 |
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Curitiba (Brazil) |
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978-3-540-88184-1 |
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GREC |
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DAG |
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no |
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DAG @ dag @ WLO2008 |
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1012 |
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Author |
Juan J. Villanueva |
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Title |
Visualization, Imaging, and Image Processing, |
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2008 |
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Proceedings of the Eight IASTED International Conference |
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Palma de Mallorca (Spain) |
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978-0-88986-759-8 |
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ISE @ ise @ Vil2008 |
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1003 |
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Author |
Jordi Gonzalez; Thomas B. Moeslund |
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Title |
Tracking Humans for the Evaluation of their Motion in Image Sequences |
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2008 |
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First International Workshop, THEMIS |
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Leeds (UK) |
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978-84-935251-9-4 |
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THEMIS |
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ISE @ ise @ GMW2008 |
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1002 |
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Author |
Joan Marti; Jose Miguel Benedi; Ana Maria Mendonça; Joan Serrat |
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Title |
Pattern Recognition and Image Analysis |
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2007 |
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3rd Iberian Conference |
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6669 |
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4477-4478 |
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Girona (Spain) |
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IbPRIA |
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ADAS @ adas @ MBM2007 |
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994 |
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Author |
Josep Llados; W. Liu; Jean-Marc Ogier |
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Title |
Seventh IAPR International Workshop on Graphics Recognition GREC 2007 |
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2007 |
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Curitiba (Brazil) |
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DAG @ dag @ LLO2007 |
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835 |
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W. Liu; Josep Llados |
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Graphics Recognition. Ten Years Review and Future Perspectives |
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2006 |
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6th International Workshop |
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3926 |
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Hong Kong (China) |
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GREC |
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DAG @ dag @ LiL2006 |
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800 |
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Author |
F. Pla; Petia Radeva; Jordi Vitria |
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Title |
Pattern Recognition: Progress, Directions and Applications |
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2006 |
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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 |
84-933652-6-2 |
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Expedition |
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Conference |
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Notes |
OR;MILAB;MV |
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no |
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Call Number |
BCNPCL @ bcnpcl @ PRV2006b |
Serial |
771 |
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