Data Fusion Methodology And Applications PDF Download
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| Author | : Marina Cocchi |
| Publisher | : Elsevier |
| Total Pages | : 396 |
| Release | : 2019-05-11 |
| Genre | : Science |
| ISBN | : 0444639853 |
Download Data Fusion Methodology and Applications Book in PDF, ePub and Kindle
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
| Author | : Veres Albert |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2017 |
| Genre | : Multisensor data fusion |
| ISBN | : 9781536127201 |
Download Data Fusion Book in PDF, ePub and Kindle
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.
| Author | : E. Shahbazian |
| Publisher | : IOS Press |
| Total Pages | : 832 |
| Release | : 2006-03-02 |
| Genre | : Computers |
| ISBN | : 1607501244 |
Download Data Fusion for Situation Monitoring, Incident Detection, Alert and Response Management Book in PDF, ePub and Kindle
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).
| Author | : Xavier Gros |
| Publisher | : Elsevier |
| Total Pages | : 233 |
| Release | : 1996-11-01 |
| Genre | : Technology & Engineering |
| ISBN | : 0080524044 |
Download NDT Data Fusion Book in PDF, ePub and Kindle
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.
| Author | : S. Pfleger |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 275 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3642849903 |
Download Data Fusion Applications Book in PDF, ePub and Kindle
Data fusion, the ability to combine data derived from several sources to provide a coherent, informative, and useful characterization of a situation,is a challenging task. There is no unified and proven solution which is applicable in all circumstances, but there are many plausible and useful approaches which can be and are used to solve particular applications. This volume presents the proceedings of the workshop Data Fusion Applications hosted in Brussels by the 1992 ESPRIT Conference and Exhibition. It contains 22 papers from 69 experts,who present advanced research results on data fusion together with practicalsolutions to multisensor data fusion in a wide variety of applications: real-time expert systems, robotics, medical diagnosis and patient surveillance, monitoring and control, marine protection, surveillance and safety in public transportation systems, image processing and interpretation, and environmental monitoring. The research forms part of the ESPRIT project DIMUS (Data Integration in Multisensor Systems).
| Author | : Xanthoula Eirini Pantazi |
| Publisher | : Academic Press |
| Total Pages | : 330 |
| Release | : 2019-10-08 |
| Genre | : Business & Economics |
| ISBN | : 0128143924 |
Download Intelligent Data Mining and Fusion Systems in Agriculture Book in PDF, ePub and Kindle
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
| Author | : James J. Clark |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 258 |
| Release | : 2013-03-09 |
| Genre | : Technology & Engineering |
| ISBN | : 1475720769 |
Download Data Fusion for Sensory Information Processing Systems Book in PDF, ePub and Kindle
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.
| Author | : David Hall |
| Publisher | : CRC Press |
| Total Pages | : 564 |
| Release | : 2001-06-20 |
| Genre | : Technology & Engineering |
| ISBN | : 1420038540 |
Download Multisensor Data Fusion Book in PDF, ePub and Kindle
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
| Author | : Ni-Bin Chang |
| Publisher | : CRC Press |
| Total Pages | : 627 |
| Release | : 2018-02-21 |
| Genre | : Technology & Engineering |
| ISBN | : 1351650637 |
Download Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing Book in PDF, ePub and Kindle
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.
| Author | : Richard T. Antony |
| Publisher | : Artech House |
| Total Pages | : 367 |
| Release | : 2015-11-01 |
| Genre | : Technology & Engineering |
| ISBN | : 1608078469 |
Download Data Fusion Support to Activity-Based Intelligence Book in PDF, ePub and Kindle
This new resource provides a coherent, intuitive, and theoretical foundation for the fusion and exploitation of traditional sensor data as well as text-based information. In addition to presenting a detailed discussion of base-level data fusion requirements, a variety of higher level exploitation algorithms are presented that perform fully automated relationship discovery, rank interest level of entities, and support context-sensitive behavior understanding (both static and dynamic context). This book identifies eight canonical fusion forms as well as twenty foundational fusion services to enable formal mapping between models and services. Normalization and representation processes for (hard) sensor data and (soft) semantic data are described as well as methods for combining hard and soft data. Included is a prototype fusion system developed to implement virtually all the presented applications in order to demonstrate the robustness and utility of the design principles presented in this resource. The prototype system presented supports a variety of user workflows and all the applications are fully integrated. There is extensive fusion system output for unclassified scenarios to permit the reader to fully understand all presented design principles. This book also presents context-sensitive fuzzy semantic spatial and temporal reasoning.
