Data Management And Internet Computing For Image Pattern Analysis


Data Management And Internet Computing For Image Pattern Analysis
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Data Management And Internet Computing For Image Pattern Analysis


Data Management And Internet Computing For Image Pattern Analysis
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Author : David D. Zhang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Data Management And Internet Computing For Image Pattern Analysis written by David D. Zhang 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 2012-12-06 with Computers categories.


Data Management and Internet Computing for Image/Pattern Analysis focuses on the data management issues and Internet computing aspect of image processing and pattern recognition research. The book presents a comprehensive overview of the state of the art, providing detailed case studies that emphasize how image and pattern (IAP) data are distributed and exchanged on sequential and parallel machines, and how the data communication patterns in low- and higher-level IAP computing differ from general numerical computation, what problems they cause and what opportunities they provide. The studies also describe how the images and matrices should be stored, accessed and distributed on different types of machines connected to the Internet, and how Internet resource sharing and data transmission change traditional IAP computing. Data Management and Internet Computing for Image/Pattern Analysis is divided into three parts: the first part describes several software approaches to IAP computing, citing several representative data communication patterns and related algorithms; the second part introduces hardware and Internet resource sharing in which a wide range of computer architectures are described and memory management issues are discussed; and the third part presents applications ranging from image coding, restoration and progressive transmission. Data Management and Internet Computing for Image/Pattern Analysis is an excellent reference for researchers and may be used as a text for advanced courses in image processing and pattern recognition.



Computational Intelligence In Healthcare 4


Computational Intelligence In Healthcare 4
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Author : Isabelle Bichindaritz
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-08

Computational Intelligence In Healthcare 4 written by Isabelle Bichindaritz 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 2010-09-08 with Computers categories.


Computational Intelligence is comparatively a new field but it has made a tremendous progress in virtually every discipline right from engineering, science, business, m- agement, aviation to healthcare. Computational intelligence already has a solid track-record of applications to healthcare, of which this book is a continuation. We would like to refer the reader to the excellent previous volumes in this series on computational intelligence in heal- care [1-3]. This book is aimed at providing the most recent advances and state of the art in the practical applications of computational intelligence paradigms in healthcare. It - cludes nineteen chapters on using various computational intelligence methods in healthcare such as intelligent agents and case-based reasoning. A number of fielded applications and case studies are presented. Highlighted are in particular novel c- putational approaches to the semantic management of health information such as in the Web 2.0, mobile agents such as in portable devices, learning agents capable of adapting to diverse clinical settings through case-based reasoning, and statistical - proaches in computational intelligence. This book is targeted towards scientists, application engineers, professors, health professionals, professors, and students. Background information on computational intelligence has been provided whenever necessary to facilitate the comprehension of a broad audience including healthcare practitioners.



Fully Tuned Radial Basis Function Neural Networks For Flight Control


Fully Tuned Radial Basis Function Neural Networks For Flight Control
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Author : N. Sundararajan
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Fully Tuned Radial Basis Function Neural Networks For Flight Control written by N. Sundararajan 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 2013-03-09 with Science categories.


Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.



Data Science New Issues Challenges And Applications


Data Science New Issues Challenges And Applications
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Author : Gintautas Dzemyda
language : en
Publisher: Springer Nature
Release Date : 2020-02-13

Data Science New Issues Challenges And Applications written by Gintautas Dzemyda and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-13 with Computers categories.


This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, knowledge storage, data stream classification, and security in social networking. The respective papers highlight a wealth of issues in, and applications of, data science. Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field. In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energy management, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.



Multisensor Decision And Estimation Fusion


Multisensor Decision And Estimation Fusion
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Author : Yunmin Zhu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Multisensor Decision And Estimation Fusion written by Yunmin Zhu 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 2012-12-06 with Technology & Engineering categories.


YUNMIN ZHU In the past two decades, multi sensor or multi-source information fusion tech niques have attracted more and more attention in practice, where observations are processed in a distributed manner and decisions or estimates are made at the individual processors, and processed data (or compressed observations) are then transmitted to a fusion center where the final global decision or estimate is made. A system with multiple distributed sensors has many advantages over one with a single sensor. These include an increase in the capability, reliability, robustness and survivability of the system. Distributed decision or estimation fusion prob lems for cases with statistically independent observations or observation noises have received significant attention (see Varshney's book Distributed Detec tion and Data Fusion, New York: Springer-Verlag, 1997, Bar-Shalom's book Multitarget-Multisensor Tracking: Advanced Applications, vol. 1-3, Artech House, 1990, 1992,2000). Problems with statistically dependent observations or observation noises are more difficult and have received much less study. In practice, however, one often sees decision or estimation fusion problems with statistically dependent observations or observation noises. For instance, when several sensors are used to detect a random signal in the presence of observation noise, the sensor observations could not be statistically independent when the signal is present. 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.



Stable Adaptive Neural Network Control


Stable Adaptive Neural Network Control
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Author : S.S. Ge
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Stable Adaptive Neural Network Control written by S.S. Ge 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 2013-03-09 with Science categories.


Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications.



Machine Interpretation Of Patterns


Machine Interpretation Of Patterns
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Author : Rajat K. De
language : en
Publisher: World Scientific
Release Date : 2010

Machine Interpretation Of Patterns written by Rajat K. De and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.


This review volume provides from both theoretical and application points of views, recent developments and state-of-the-art reviews in various areas of pattern recognition, image processing, machine learning, soft computing, data mining and web intelligence. Machine Interpretation of Patterns: Image Analysis and Data Mining is an essential and invaluable resource for professionals and advanced graduates in computer science, mathematics and life sciences. It can also be considered as an integrated volume to researchers interested in doing interdisciplinary research where computer science is a component.



Advanced Sensing In Image Processing And Iot


Advanced Sensing In Image Processing And Iot
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Author : Rashmi Gupta
language : en
Publisher: CRC Press
Release Date : 2021-03-26

Advanced Sensing In Image Processing And Iot written by Rashmi Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-26 with Computers categories.


The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations. Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.



Healthcare Data Analytics And Management


Healthcare Data Analytics And Management
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-11-15

Healthcare Data Analytics And Management written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-15 with Science categories.


Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges



Spatiotemporal Data Analytics And Modeling


Spatiotemporal Data Analytics And Modeling
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Author : John A
language : en
Publisher: Springer Nature
Release Date :

Spatiotemporal Data Analytics And Modeling written by John A and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.