Multisensor Fusion (NATO Science Series II: Mathematics, Physics and Chemistry)



Publisher: Springer

Written in English
Cover of: Multisensor Fusion (NATO Science Series II: Mathematics, Physics and Chemistry) |
Published: Pages: 960 Downloads: 367
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Subjects:

  • Machine learning,
  • Neurosciences,
  • Robotics,
  • Remote Sensing,
  • Detectors,
  • Electronic Apparatus And Devices,
  • Computers,
  • Technology & Industrial Arts,
  • Multisensor data fusion,
  • Computer Books: General,
  • Multiple criteria decision mak,
  • Computers / Artificial Intelligence,
  • Database Management - Database Mining,
  • Congresses,
  • Intelligent control systems

Edition Notes

ContributionsAnthony K. Hyder (Editor), E. Shahbazian (Editor), E. Waltz (Editor)
The Physical Object
FormatHardcover
Number of Pages960
ID Numbers
Open LibraryOL8370150M
ISBN 101402007221
ISBN 109781402007224

The minimal representation approach to multisensor fusion is based on the use of an information measure as a universal yardstick for fusion. Using models of sensor uncertainty, the representation size guides the integration of widely varying types of data and maximizes the information contributed to a consistent interpretation. Multi-Sensor Data Fusion with MATLAB - Ebook written by Jitendra R. Raol. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Multi-Sensor Data Fusion with MATLAB. Data fusion is the process of integrating multiple data sources to produce more consistent, accurate, and useful information than that provided by any individual data source.. Data fusion processes are often categorized as low, intermediate, or high, depending on the processing stage at which fusion takes place. Low-level data fusion combines several sources of raw data to produce new raw data. Multisensor Fusion Estimation Theory and Application, Hardcover by Yan, Liping; Lu, Jiang; Xia, Yuanqing, ISBN , ISBN , Like New Used, Free shipping in the US. This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 Rating: % positive.

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Multisensor Fusion (NATO Science Series II: Mathematics, Physics and Chemistry) Download PDF EPUB FB2

If you're interested or are in the information fusion field you must have this book. Expanded from the 1st edition, this book keeps and enhances the chapters in the first book, yet adds many important new ones, especially in the pragmatic implementation of information fusion.

You must read the chapter by Dr. Steinberg on fusion applications/5(3). Multisensor Data Fusion (Artech House Radar Library (Hardcover)) Illustrated Edition by Edward L. Waltz (Author), James Llinas (Author), Franklin E. White Jr. Cited by: Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies.

The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution. Book Description Multisensor Data Fusion: From Algorithms and Architectural Design to Applicationscovers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines.

The book examines the underlying principles of sensor operation and data fusion, the techniques and technologies that enable the process, including the operation of 'fusion engines'.

Fundamental theory and the enabling technologies of data fusion are presented in a systematic and accessible manner. Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies.

The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.

Multisensor Data Fusion (Electrical Engineering & Applied Multisensor Fusion book Processing Series Book 3) - Kindle Multisensor Fusion book by Hall, David, Llinas, James, Hall, David, Llinas, James.

Download it once and read it on your Kindle device, PC, phones or tablets/5(3). The book examines the underlying principles of sensor operation and data fusion, the techniques and technologies that enable the process, including the operation of 'fusion engines. This book provides a more complete treatment of the fundamentals of multi­ sensor decision and estimation fusion in order to deal with general random ob­ servations or observation noises that are correlated across the sensors.

Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition represents the most current concepts and theory as information fusion expands into. Multisensor data fusion: from algorithms and architectural design to applications | Fourati, Hassen; Iniewski, Krzysztof | download | Z-Library.

Download books for free. Find books. If you're interested or are in the information fusion field you must have this book. Expanded from the 1st edition, this book keeps and enhances the chapters in the first book, yet adds many important new ones, especially in the pragmatic implementation of information fusion.

You must read the chapter by Dr. Steinberg on fusion applications. CRC Press, - Technology & Engineering - pages 0 Reviews The emerging technology of multisensor data fusion has a wide range of applications, both in.

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 Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies.

About this book Addressing recent challenges and developments in this growing field, Multisensor Data Fusion Uncertainty Theory first discusses basic questions such as: Why and when is multiple sensor fusion necessary.

Multisensor data fusion is a technology to enable combining information from several sources in order to form a unified picture. Data fusion systems are now widely used in various areas such as sensor networks, robotics, video and image processing, and intelligent system design, to name a few.

Multisensor Fusion for Object Recognition -- Fusion of Range and Intensity Image Data for Recognition of 3D Object Surfaces \/ Jianchi Wei, Paul Levi and Ulrich Rembold -- Integrating Driving Model and Depth for Identification of Partially Occluded 3D Models \/ A. Sanfeliu, M. Ananos and M.J.

Dunjo -- Fusion of Color and Geometric Information. Siaterlis C and Maglaris B Towards multisensor data fusion for DoS detection Proceedings of the ACM symposium on Applied computing, () Yager R () A framework for multi-source data fusion, Information Sciences: an International Journal.

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.

The book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensingoffers complete understanding of the basic scientific principles needed to perform image processing, gap filling, data merging, data fusion, machine learning, and feature extraction. Decision-level fusion is a high-level fusion.

For utilization of multisensor data, fuzzy control technology and artificial neural network technology can be used. View chapter Purchase book. 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 3/5(2).

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. Over the past two decades, signi cant attention has been focused on multisensor data fusion for both military and nonmilitary applications. Data fusion techniques combine data from multiple sensors and related information to achieve more speci c inferences than could be achieved by using a single, independent sensor.

This book is an important introduction to multisensor data fusion technology and its application in military command, control, and intelligence operations. The presentation is given at a system-level.

Get this from a library. Multisensor Fusion. [A K Hyder; E Shahbazian; E Waltz] -- For some time, all branches of the military have used a wide range of sensors to provide data for many purposes, including surveillance, reconnoitring, target detection and battle damage assessment.

What is the purpose and the specificity of information fusion processing in multiple sensor systems. Considering the different uncertainty formalisms, a set of coherent operators corresponding to the different steps of a complete fusion process is then developed, in order to meet the requirements identified in the first part of the book.

The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability.

The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. Siaterlis C and Maglaris B Towards multisensor data fusion for DoS detection Proceedings of the ACM symposium on Applied computing, () Achalakul T and Taylor S () A distributed spectral-screening PCT algorithm, Journal of Parallel and Distributed Computing,(), Online publication date: 1-Mar.

Multisensor Data Fusion, 2 Volume Set | David L. Hall, James Llinas | download | B–OK. Download books for free. Find books.Multi-Sensor Data Fusion with Jitendra Raol Buy from $ Handbook of Multisensor Data Martin Liggins II (Editor), David Hall (Editor) Buy from $ Multisensor data fusion.

Waltz, Llinas Buy from $ Distributed Sensor Networks. S Sitharama Iyengar (Editor), Richard R Brooks (Editor) Buy from $ Multisensor Fusion.This volume contains revised papers based on contributions to the NATO Advanced Research Workshop on Multisensor Fusion for Computer Vision, held in Grenoble, France, in June The 24 papers presented here cover a broad range of topics, including the principles and issues in multisensor fusion.