Data Fusion: Concepts and Ideas

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Publisher : Springer Science & Business Media
ISBN 13 : 3642272223
Total Pages : 349 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Data Fusion: Concepts and Ideas by : H B Mitchell

Download or read book Data Fusion: Concepts and Ideas written by H B Mitchell and published by Springer Science & Business Media. This book was released on 2012-02-09 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to the concepts and idea of multisensor data fusion. It is an extensively revised second edition of the author's successful book: "Multi-Sensor Data Fusion: An Introduction" which was originally published by Springer-Verlag in 2007. The main changes in the new book are: New Material: Apart from one new chapter there are approximately 30 new sections, 50 new examples and 100 new references. At the same time, material which is out-of-date has been eliminated and the remaining text has been rewritten for added clarity. Altogether, the new book is nearly 70 pages longer than the original book. Matlab code: Where appropriate we have given details of Matlab code which may be downloaded from the worldwide web. In a few places, where such code is not readily available, we have included Matlab code in the body of the text. Layout. The layout and typography has been revised. Examples and Matlab code now appear on a gray background for easy identification and advancd material is marked with an asterisk. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familarity with the basic tools of linear algebra, calculus and simple probability is recommended. Although conceptually simple, the study of mult-sensor data fusion presents challenges that are unique within the education of the electrical engineer or computer scientist. To become competent in the field the student must become familiar with tools taken from a wide range of diverse subjects including: neural networks, signal processing, statistical estimation, tracking algorithms, computer vision and control theory. All too often, the student views multi-sensor data fusion as a miscellaneous assortment of different processes which bear no relationship to each other. In contrast, in this book the processes are unified by using a common statistical framework. As a consequence, the underlying pattern of relationships that exists between the different methodologies is made evident. The book is illustrated with many real-life examples taken from a diverse range of applications and contains an extensive list of modern references.

Sensor and Data Fusion

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Publisher : SPIE Press
ISBN 13 : 9780819454355
Total Pages : 346 pages
Book Rating : 4.4/5 (543 download)

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Book Synopsis Sensor and Data Fusion by : Lawrence A. Klein

Download or read book Sensor and Data Fusion written by Lawrence A. Klein and published by SPIE Press. This book was released on 2004 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book illustrates the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance. Applications that benefit from this technology include: vehicular traffic management, remote sensing, target classification and tracking- weather forecasting- military and homeland defense. Covering data fusion algorithms in detail, Klein includes a summary of the information required to implement each of the algorithms discussed, and outlines system application scenarios that may limit sensor size but that require high resolution data.

Data Fusion Methodology and Applications

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Publisher : Elsevier
ISBN 13 : 0444639853
Total Pages : 396 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Data Fusion Methodology and Applications by : Marina Cocchi

Download or read book Data Fusion Methodology and Applications written by Marina Cocchi and published by Elsevier. This book was released on 2019-05-11 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Multisensor Data Fusion

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Publisher : CRC Press
ISBN 13 : 1420038540
Total Pages : 564 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Multisensor Data Fusion by : David Hall

Download or read book Multisensor Data Fusion written by David Hall and published by CRC Press. This book was released on 2001-06-20 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 evolut

Multi-Sensor Data Fusion

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Publisher : Springer Science & Business Media
ISBN 13 : 3540715592
Total Pages : 281 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Multi-Sensor Data Fusion by : H.B. Mitchell

Download or read book Multi-Sensor Data Fusion written by H.B. Mitchell and published by Springer Science & Business Media. This book was released on 2007-07-13 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. It is aimed at advanced undergraduate and first-year graduate students in electrical engineering and computer science, as well as researchers and professional engineers. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familiarity with the basic tools of linear algebra, calculus and simple probability theory is recommended.

Principles of Data Fusion Automation

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Publisher : Artech House Publishers
ISBN 13 : 9780890067604
Total Pages : 0 pages
Book Rating : 4.0/5 (676 download)

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Book Synopsis Principles of Data Fusion Automation by : Richard T. Antony

Download or read book Principles of Data Fusion Automation written by Richard T. Antony and published by Artech House Publishers. This book was released on 1995 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written with a minimum of technical jargon, this unique, easy-to-understand book strengthens your understanding of the key principles behind efficient approaches to data fusion problem-solving and database management system design, and connects these principles to help you design better, more effective fusion algorithms.

Data Fusion in Robotics & Machine Intelligence

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Publisher : Academic Press
ISBN 13 : 0323138357
Total Pages : 546 pages
Book Rating : 4.3/5 (231 download)

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Book Synopsis Data Fusion in Robotics & Machine Intelligence by : Gerard Meurant

Download or read book Data Fusion in Robotics & Machine Intelligence written by Gerard Meurant and published by Academic Press. This book was released on 1992-10-12 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the techniques for modeling and integration of data provided by different sensors within robotics and knowledge sources within machine intelligence. Leaders in robotics and machine intelligence capture state-of-the-art technology in data sensor fusion and give a unified vision of the future of the field, presented from both the theoretical and practical angles.

Multi-Sensor Data Fusion with MATLAB

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Author :
Publisher : CRC Press
ISBN 13 : 1439800057
Total Pages : 570 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Multi-Sensor Data Fusion with MATLAB by : Jitendra R. Raol

Download or read book Multi-Sensor Data Fusion with MATLAB written by Jitendra R. Raol and published by CRC Press. This book was released on 2009-12-16 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly

Mathematics of Data Fusion

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Publisher : Springer Science & Business Media
ISBN 13 : 9401589291
Total Pages : 503 pages
Book Rating : 4.4/5 (15 download)

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Book Synopsis Mathematics of Data Fusion by : I.R. Goodman

Download or read book Mathematics of Data Fusion written by I.R. Goodman and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data fusion or information fusion are names which have been primarily assigned to military-oriented problems. In military applications, typical data fusion problems are: multisensor, multitarget detection, object identification, tracking, threat assessment, mission assessment and mission planning, among many others. However, it is clear that the basic underlying concepts underlying such fusion procedures can often be used in nonmilitary applications as well. The purpose of this book is twofold: First, to point out present gaps in the way data fusion problems are conceptually treated. Second, to address this issue by exhibiting mathematical tools which treat combination of evidence in the presence of uncertainty in a more systematic and comprehensive way. These techniques are based essentially on two novel ideas relating to probability theory: the newly developed fields of random set theory and conditional and relational event algebra. This volume is intended to be both an update on research progress on data fusion and an introduction to potentially powerful new techniques: fuzzy logic, random set theory, and conditional and relational event algebra. Audience: This volume can be used as a reference book for researchers and practitioners in data fusion or expert systems theory, or for graduate students as text for a research seminar or graduate level course.

Kernel-based Data Fusion for Machine Learning

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Publisher : Springer
ISBN 13 : 3642194060
Total Pages : 214 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Kernel-based Data Fusion for Machine Learning by : Shi Yu

Download or read book Kernel-based Data Fusion for Machine Learning written by Shi Yu and published by Springer. This book was released on 2011-03-29 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Fusion for Sensory Information Processing Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 1475720769
Total Pages : 258 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Data Fusion for Sensory Information Processing Systems by : James J. Clark

Download or read book Data Fusion for Sensory Information Processing Systems written by James J. Clark and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: The science associated with the development of artificial sen sory systems is occupied primarily with determining how information about the world can be extracted from sensory data. For example, computational vision is, for the most part, concerned with the de velopment of algorithms for distilling information about the world and recognition of various objects in the environ (e. g. localization ment) from visual images (e. g. photographs or video frames). There are often a multitude of ways in which a specific piece of informa tion about the world can be obtained from sensory data. A subarea of research into sensory systems has arisen which is concerned with methods for combining these various information sources. This field is known as data fusion, or sensor fusion. The literature on data fusion is extensive, indicating the intense interest in this topic, but is quite chaotic. There are no accepted approaches, save for a few special cases, and many of the best methods are ad hoc. This book represents our attempt at providing a mathematical foundation upon which data fusion algorithms can be constructed and analyzed. The methodology that we present in this text is mo tivated by a strong belief in the importance of constraints in sensory information processing systems. In our view, data fusion is best un derstood as the embedding of multiple constraints on the solution to a sensory information processing problem into the solution pro cess.

Mathematical Techniques in Multisensor Data Fusion

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Publisher : Artech House
ISBN 13 : 9781580533355
Total Pages : 470 pages
Book Rating : 4.5/5 (333 download)

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Book Synopsis Mathematical Techniques in Multisensor Data Fusion by : David Lee Hall

Download or read book Mathematical Techniques in Multisensor Data Fusion written by David Lee Hall and published by Artech House. This book was released on 2004 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition of this book, advances in algorithms, logic and software tools have transformed the field of data fusion. The latest edition covers these areas as well as smart agents, human computer interaction, cognitive aides to analysis and data system fusion control. data fusion system, this book guides you through the process of determining the trade-offs among competing data fusion algorithms, selecting commercial off-the-shelf (COTS) tools, and understanding when data fusion improves systems processing. Completely new chapters in this second edition explain data fusion system control, DARPA's recently developed TRIP model, and the latest applications of data fusion in data warehousing and medical equipment, as well as defence systems.

Distributed Detection and Data Fusion

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Publisher : Springer Science & Business Media
ISBN 13 : 1461219043
Total Pages : 286 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Distributed Detection and Data Fusion by : Pramod K. Varshney

Download or read book Distributed Detection and Data Fusion written by Pramod K. Varshney and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introductory treatment of the fundamentals of decision-making in a distributed framework. Classical detection theory assumes that complete observations are available at a central processor for decision-making. More recently, many applications have been identified in which observations are processed in a distributed manner and decisions are made at the distributed processors, or processed data (compressed observations) are conveyed to a fusion center that makes the global decision. Conventional detection theory has been extended so that it can deal with such distributed detection problems. A unified treatment of recent advances in this new branch of statistical decision theory is presented. Distributed detection under different formulations and for a variety of detection network topologies is discussed. This material is not available in any other book and has appeared relatively recently in technical journals. The level of presentation is such that the hook can be used as a graduate-level textbook. Numerous examples are presented throughout the book. It is assumed that the reader has been exposed to detection theory. The book will also serve as a useful reference for practicing engineers and researchers. I have actively pursued research on distributed detection and data fusion over the last decade, which ultimately interested me in writing this book. Many individuals have played a key role in the completion of this book.

Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 1461413494
Total Pages : 120 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks by : Ahmed Abdelgawad

Download or read book Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks written by Ahmed Abdelgawad and published by Springer Science & Business Media. This book was released on 2012-02-15 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative. Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.

Data Fusion in Information Retrieval

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Publisher : Springer Science & Business Media
ISBN 13 : 3642288669
Total Pages : 234 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Data Fusion in Information Retrieval by : Shengli Wu

Download or read book Data Fusion in Information Retrieval written by Shengli Wu and published by Springer Science & Business Media. This book was released on 2012-04-05 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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Publisher : CRC Press
ISBN 13 : 1439860335
Total Pages : 498 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Distributed Data Fusion for Network-Centric Operations by : David Hall

Download or read book Distributed Data Fusion for Network-Centric Operations written by David Hall and published by CRC Press. This book was released on 2017-12-19 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Tracking and Sensor Data Fusion

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Publisher : Springer Science & Business Media
ISBN 13 : 3642392717
Total Pages : 253 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Tracking and Sensor Data Fusion by : Wolfgang Koch

Download or read book Tracking and Sensor Data Fusion written by Wolfgang Koch and published by Springer Science & Business Media. This book was released on 2013-09-20 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, reliability, or cost. This book provides an introduction Sensor Data Fusion, as an information technology as well as a branch of engineering science and informatics. Part I presents a coherent methodological framework, thus providing the prerequisites for discussing selected applications in Part II of the book. The presentation mirrors the author's views on the subject and emphasizes his own contributions to the development of particular aspects. With some delay, Sensor Data Fusion is likely to develop along lines similar to the evolution of another modern key technology whose origin is in the military domain, the Internet. It is the author's firm conviction that until now, scientists and engineers have only scratched the surface of the vast range of opportunities for research, engineering, and product development that still waits to be explored: the Internet of the Sensors.