Data Fusion Methodology and Applications

Data Fusion Methodology and Applications

Author: Marina Cocchi

Publisher: Elsevier

Published: 2019-05-11

Total Pages: 398

ISBN-13: 0444639853

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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

Data Fusion

Author: Veres Albert

Publisher:

Published: 2017

Total Pages: 0

ISBN-13: 9781536127201

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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.


NDT Data Fusion

NDT Data Fusion

Author: Xavier Gros

Publisher: Elsevier

Published: 1996-11-01

Total Pages: 233

ISBN-13: 0080524044

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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.


Intelligent Data Mining and Fusion Systems in Agriculture

Intelligent Data Mining and Fusion Systems in Agriculture

Author: Xanthoula-Eirini Pantazi

Publisher: Academic Press

Published: 2019-10-08

Total Pages: 334

ISBN-13: 0128143924

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Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms. - Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (IoTs) in agriculture - Addresses AI use in weed management, disease detection, yield prediction and crop production - Utilizes case studies to provide real-world insights and direction


Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Author: Ni-Bin Chang

Publisher: CRC Press

Published: 2018-02-21

Total Pages: 627

ISBN-13: 1351650637

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In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. 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. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.


Multisensor Data Fusion

Multisensor Data Fusion

Author: David Hall

Publisher: CRC Press

Published: 2001-06-20

Total Pages: 564

ISBN-13: 1420038540

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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


Information Technology in Geo-Engineering

Information Technology in Geo-Engineering

Author: António Gomes Correia

Publisher: Springer Nature

Published: 2019-09-24

Total Pages: 925

ISBN-13: 3030320294

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These proceedings address the latest developments in information communication and technologies for geo-engineering. The 3rd International Conference on Information Technology in Geo-Engineering (ICITG 2019), held in Guimarães, Portugal, follows the previous successful installments of this conference series in Durham (2014) and Shanghai (2010). The respective chapters cover the following: Use of information and communications technologies Big data and databases Data mining and data science Imaging technologies Building information modelling applied to geo-structures Artificial intelligence Smart geomaterials and intelligent construction Sensors and monitoring Asset management Case studies on design, construction and maintenance Given its broad range of coverage, the book will benefit students, educators, researchers and professional practitioners alike, encouraging these readers to help take the geo-engineering community into the digital age


Data Fusion

Data Fusion

Author: Lucien Wald

Publisher: Presses des MINES

Published: 2002

Total Pages: 53

ISBN-13: 291176238X

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This book establishes the fundamentals (particularly definitions and architectures) in data fusion. The second part of the book is devoted to methods for the fusion of images. It offers an in-depth presentation of standard and advanced methods for the fusion of multi-modality images.


Body Sensor Networks

Body Sensor Networks

Author: Guang-Zhong Yang

Publisher: Springer

Published: 2014-04-16

Total Pages: 572

ISBN-13: 1447163745

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The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vivo monitoring and intervention. A myriad of platforms are now available from both academic institutions and commercial organisations. They permit the management of patients with both acute and chronic symptoms, including diabetes, cardiovascular diseases, treatment of epilepsy and other debilitating neurological disorders. Despite extensive developments in sensing technologies, there are significant research issues related to system integration, sensor miniaturisation, low-power sensor interface, wireless telemetry and signal processing. In the 2nd edition of this popular and authoritative reference on Body Sensor Networks (BSN), major topics related to the latest technological developments and potential clinical applications are discussed, with contents covering. Biosensor Design, Interfacing and Nanotechnology Wireless Communication and Network Topologies Communication Protocols and Standards Energy Harvesting and Power Delivery Ultra-low Power Bio-inspired Processing Multi-sensor Fusion and Context Aware Sensing Autonomic Sensing Wearable, Ingestible Sensor Integration and Exemplar Applications System Integration and Wireless Sensor Microsystems The book also provides a comprehensive review of the current wireless sensor development platforms and a step-by-step guide to developing your own BSN applications through the use of the BSN development kit.


Data Fusion for Sensory Information Processing Systems

Data Fusion for Sensory Information Processing Systems

Author: James J. Clark

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 258

ISBN-13: 1475720769

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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.