Data Fusion Methodology And Applications
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Data Fusion Methodology And Applications
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Author : Marina Cocchi
language : en
Publisher: Elsevier
Release Date : 2019-05-11
Data Fusion Methodology And Applications written by Marina Cocchi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-11 with Science categories.
Data Fusion Methodology and Applications explores the data-driven discovery paradigm in science and the need to handle large amounts of diverse data. Drivers of this change include the increased availability and accessibility of hyphenated analytical platforms, imaging techniques, the explosion of omics data, and the development of information technology. As data-driven research deals with an inductive attitude that aims to extract information and build models capable of inferring the underlying phenomena from the data itself, this book explores the challenges and methodologies used to integrate data from multiple sources, analytical platforms, different modalities, and varying timescales. Presents the first comprehensive textbook on data fusion, focusing on all aspects of data-driven discovery Includes comprehensible, theoretical chapters written for large and diverse audiences Provides a wealth of selected application to the topics included
Data Fusion
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Author : Veres Albert
language : en
Publisher:
Release Date : 2017
Data Fusion written by Veres Albert and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Multisensor data fusion categories.
In the first chapter, Sergey A Sakulin, Ph.D. and Alexander N Alfimtsev, Ph.D. discuss fuzzy integral, a powerful metaoperator, and its applications. In the second chapter, Bruno G Botelho and Adriana S Franca discuss the concept of data fusion and how it might be applied in different areas of food analysis to improve the information range regarding samples. In the third and final chapter, Carlo Quaranta and Giorgio Balzarotti compare a new data fusion equation with an approach that has been familiarised in previous literature.
Data Fusion For Situation Monitoring Incident Detection Alert And Response Management
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Author : E. Shahbazian
language : en
Publisher: IOS Press
Release Date : 2006-03-02
Data Fusion For Situation Monitoring Incident Detection Alert And Response Management written by E. Shahbazian and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-02 with Computers categories.
Data Fusion is a very broad interdisciplinary technology domain. It provides techniques and methods for; integrating information from multiple sources and using the complementarities of these detections to derive maximum information about the phenomenon being observed; analyzing and deriving the meaning of these observations and predicting possible consequences of the observed state of the environment; selecting the best course of action; and controlling the actions. Here, the focus is on the more mature phase of data fusion, namely the detection and identification / classification of phenomena being observed and exploitation of the related methods for Security-Related Civil Science and Technology (SST) applications. It is necessary to; expand on the data fusion methodology pertinent to Situation Monitoring, Incident Detection, Alert and Response Management; discuss some related Cognitive Engineering and visualization issues; provide an insight into the architectures and methodologies for building a data fusion system; discuss fusion approaches to image exploitation with emphasis on security applications; discuss novel distributed tracking approaches as a necessary step of situation monitoring and incident detection; and provide examples of real situations, in which data fusion can enhance incident detection, prevention and response capability. In order to give a logical presentation of the data fusion material, first the general concepts are highlighted (Fusion Methodology, Human Computer Interactions and Systems and Architectures), closing with several applications (Data Fusion for Imagery, Tracking and Sensor Fusion and Applications and Opportunities for Fusion).
Data Fusion
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Author :
language : en
Publisher:
Release Date : 2015
Data Fusion written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Kernel Based Data Fusion For Machine Learning
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Author : Shi Yu
language : en
Publisher: Springer
Release Date : 2011-03-29
Kernel Based Data Fusion For Machine Learning written by Shi Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-29 with Technology & Engineering categories.
Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Rayleigh quotient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
Ndt Data Fusion
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Author : Xavier Gros
language : en
Publisher: Elsevier
Release Date : 1996-11-01
Ndt Data Fusion written by Xavier Gros and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-11-01 with Technology & Engineering categories.
Data fusion is a rapidly developing technology which involves the combination of information supplied by several NDT (Non-Destructive Testing) sensors to provide a more complete and understandable picture of structural integrity. This text is the first to be devoted exclusively to the concept of multisensor integration and data fusion applied to NDT. The advantages of this methodology are widely acknowledged and the author presents an excellent introduction to data fusion processes. Problems are approached progressively through detailed case studies, offering practical guidance for those wishing to develop and explore NDT data fusion further. This book will prove invaluable to inspectors, students and researchers concerned with NDT signal processing measurements and testing. It shows the great value and major benefits which can be achieved by implementing multisensor data fusion, not only in NDT but also in any discipline where measurements and testing are key activities.
High Level Data Fusion
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Author : Subrata Kumar Das
language : en
Publisher: Artech House Publishers
Release Date : 2008
High Level Data Fusion written by Subrata Kumar Das and has been published by Artech House Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
"This resource provides comprehensive details on cutting-edge data fusion techniques that help professionals develop powerful situation assessment services with eye-popping capabilities and performance. This book explores object and situation fusion processes with an appropriate handling of uncertainties. Moreover, it applies cutting-edge artificial intelligence and emergency technologies like particle filtering, spatiotemporal clustering, net-centricity, agent formalism, and distributed fusion together with essential Level 1 and 2 fusion techniques. Professionals discover all the tools they need to design high-level fusion services, select algorithms and software, simulate performance, and evaluate systems with never-before effectiveness."--BOOK JACKET.
Multisensor Data Fusion
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Author : David Hall
language : en
Publisher: CRC Press
Release Date : 2001-06-20
Multisensor Data Fusion written by David Hall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-06-20 with Technology & Engineering categories.
The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolution of computers and the maturation of data fusion technology, the door to using data fusion in everyday applications is now wide open and presenting great opportunities. The Handbook of Multisensor Data Fusion provides a unique, comprehensive, and up-to-date resource for data fusion systems designers and researchers. Divided into five parts, it: offers a thorough introduction to data fusion terminology and models describes advanced techniques for data association, target tracking, and identification presents practical information on system development, including requirements analysis, systems engineering, algorithm selection, database design, human-computer interfaces, and performance assessment introduces applications from the DoD, NASA, DARPA, and condition-based monitoring of complex machinery supplies data fusion resources and Web sites The contributing authors are all recognized leaders in data fusion and have collaborated to provide what promises to be the definitive reference for this rapidly developing field. Whether you are a researcher, system designer, implementer, or student, in the Handbook of Multisensor Data Fusion you'll find everything you need, from a basic introduction and survey of data fusion technology to advanced mathematics and theory, including very practical advice on data fusion system development and implementation.
Data Fusion In Information Retrieval
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Author : Shengli Wu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-04-05
Data Fusion In Information Retrieval written by Shengli Wu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-05 with Technology & Engineering categories.
The technique of data fusion has been used extensively in information retrieval due to the complexity and diversity of tasks involved such as web and social networks, legal, enterprise, and many others. This book presents both a theoretical and empirical approach to data fusion. Several typical data fusion algorithms are discussed, analyzed and evaluated. A reader will find answers to the following questions, among others: What are the key factors that affect the performance of data fusion algorithms significantly? What conditions are favorable to data fusion algorithms? CombSum and CombMNZ, which one is better? and why? What is the rationale of using the linear combination method? How can the best fusion option be found under any given circumstances?
Distributed Data Fusion For Network Centric Operations
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Author : David Hall
language : en
Publisher: CRC Press
Release Date : 2017-12-19
Distributed Data Fusion For Network Centric Operations written by David Hall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Computers categories.
With the recent proliferation of service-oriented architectures (SOA), cloud computing technologies, and distributed-interconnected systems, distributed fusion is taking on a larger role in a variety of applications—from environmental monitoring and crisis management to intelligent buildings and defense. Drawing on the work of leading experts around the world, Distributed Data Fusion for Network-Centric Operations examines the state of the art of data fusion in a distributed sensing, communications, and computing environment. Get Insight into Designing and Implementing Data Fusion in a Distributed Network Addressing the entirety of information fusion, the contributors cover everything from signal and image processing, through estimation, to situation awareness. In particular, the work offers a timely look at the issues and solutions involving fusion within a distributed network enterprise. These include critical design problems, such as how to maintain a pedigree of agents or nodes that receive information, provide their contribution to the dataset, and pass to other network components. The book also tackles dynamic data sharing within a network-centric enterprise, distributed fusion effects on state estimation, graph-theoretic methods to optimize fusion performance, human engineering factors, and computer ontologies for higher levels of situation assessment. A comprehensive introduction to this emerging field and its challenges, the book explores how data fusion can be used within grid, distributed, and cloud computing architectures. Bringing together both theoretical and applied research perspectives, this is a valuable reference for fusion researchers and practitioners. It offers guidance and insight for those working on the complex issues of designing and implementing distributed, decentralized information fusion.