Data Variant Kernel Analysis

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Data Variant Kernel Analysis

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Author : Yuichi Motai
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-27

Data Variant Kernel Analysis written by Yuichi Motai and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-27 with Computers categories.

Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include data formations of offline, distributed, online, cloud, and longitudinal data, used for kernel analysis to classify and predict future state. Data-Variant Kernel Analysis: Surveys the kernel analysis in the traditionally developed machine learning techniques, such as Neural Networks (NN), Support Vector Machines (SVM), and Principal Component Analysis (PCA) Develops group kernel analysis with the distributed databases to compare speed and memory usages Explores the possibility of real-time processes by synthesizing offline and online databases Applies the assembled databases to compare cloud computing environments Examines the prediction of longitudinal data with time-sequential configurations Data-Variant Kernel Analysis is a detailed reference for graduate students as well as electrical and computer engineers interested in pattern analysis and its application in colon cancer detection.

Artificial Intelligence And Smart Agriculture Technology

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Author : Utku Kose
language : en
Publisher: CRC Press
Release Date : 2022-06-27

Artificial Intelligence And Smart Agriculture Technology written by Utku Kose and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-27 with Computers categories.

This book was created with the intention of informing an international audience about the latest technological aspects for developing smart agricultural applications. As artificial intelligence (AI) takes the main role in this, the majority of the chapters are associated with the role of AI and data analytics components for better agricultural applications. The first two chapters provide alternative, wide reviews of the use of AI, robotics, and the Internet of Things as effective solutions to agricultural problems. The third chapter looks at the use of blockchain technology in smart agricultural scenarios. In the fourth chapter, a future view is provided of an Internet of Things-oriented sustainable agriculture. Next, the fifth chapter provides a governmental evaluation of advanced farming technologies, and the sixth chapter discusses the role of big data in smart agricultural applications. The role of the blockchain is evaluated in terms of an industrial view under the seventh chapter, and the eighth chapter provides a discussion of data mining and data extraction, which is essential for better further analysis by smart tools. The ninth chapter evaluates the use of machine learning in food processing and preservation, which is a critical issue for dealing with issues concerns regarding insufficient foud sources. The tenth chapter also discusses sustainability, and the eleventh chapter focuses on the problem of plant disease prediction, which is among the critical agricultural issues. Similarly, the twelfth chapter considers the use of deep learning for classifying plant diseases. Finally, the book ends with a look at cyber threats to farming automation in the thirteenth chapter and a case study of India for a better, smart, and sustainable agriculture in the fourteenth chapter. This book presents the most critical research topics of today’s smart agricultural applications and provides a valuable view for both technological knowledge and ability that will be helpful to academicians, scientists, students who are the future of science, and industrial practitioners who collaborate with academia.

Kernel Methods In Computational Biology

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Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 2004

Kernel Methods In Computational Biology written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.

A detailed overview of current research in kernel methods and their application to computational biology.

Visual Data Exploration And Analysis

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Author :
language : en
Publisher:
Release Date : 1995

Visual Data Exploration And Analysis written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Digital computer simulation categories.

Data Variant Kernel Analysis

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Author : Yuichi Motai
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-13

Data Variant Kernel Analysis written by Yuichi Motai and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-13 with Computers categories.

Describes and discusses the variants of kernel analysismethods for data types that have been intensely studied in recentyears This book covers kernel analysis topics ranging from thefundamental theory of kernel functions to its applications. Thebook surveys the current status, popular trends, and developmentsin kernel analysis studies. The author discusses multiple kernellearning algorithms and how to choose the appropriate kernelsduring the learning phase. Data-Variant Kernel Analysis is anew pattern analysis framework for different types of dataconfigurations. The chapters include data formations of offline,distributed, online, cloud, and longitudinal data, used for kernelanalysis to classify and predict future state. Data-Variant Kernel Analysis: Surveys the kernel analysis in the traditionally developedmachine learning techniques, such as Neural Networks (NN), SupportVector Machines (SVM), and Principal Component Analysis (PCA) Develops group kernel analysis with the distributed databasesto compare speed and memory usages Explores the possibility of real-time processes by synthesizingoffline and online databases Applies the assembled databases to compare cloud computingenvironments Examines the prediction of longitudinal data withtime-sequential configurations Data-Variant Kernel Analysis is a detailed reference forgraduate students as well as electrical and computer engineersinterested in pattern analysis and its application in colon cancerdetection.

Machine Learning Based Sequence Analysis Bioinformatics And Nanopore Transduction Detection

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Author : Stephen Winters-Hilt
language : en
Publisher: Lulu.com
Release Date : 2011-05-01

Machine Learning Based Sequence Analysis Bioinformatics And Nanopore Transduction Detection written by Stephen Winters-Hilt and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-01 with Computers categories.

This is intended to be a simple and accessible book on machine learning methods and their application in computational genomics and nanopore transduction detection. This book has arisen from eight years of teaching one-semester courses on various machine-learning, cheminformatics, and bioinformatics topics. The book begins with a description of ad hoc signal acquisition methods and how to orient on signal processing problems with the standard tools from information theory and signal analysis. A general stochastic sequential analysis (SSA) signal processing architecture is then described that implements Hidden Markov Model (HMM) methods. Methods are then shown for classification and clustering using generalized Support Vector Machines, for use with the SSA Protocol, or independent of that approach. Optimization metaheuristics are used for tuning over algorithmic parameters throughout. Hardware implementations and short code examples of the various methods are also described.

Computer Vision And Image Processing

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Author : Neeta Nain
language : en
Publisher: Springer Nature
Release Date : 2020-03-28

Computer Vision And Image Processing written by Neeta Nain and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-28 with Computers categories.

This two-volume set (CCIS 1147, CCIS 1148) constitutes the refereed proceedings of the 4th International Conference on Computer Vision and Image Processing. held in Jaipur, India, in September 2019. The 73 full papers and 10 short papers were carefully reviewed and selected from 202 submissions. The papers are organized by the topical headings in two parts. Part I: Biometrics; Computer Forensic; Computer Vision; Dimension Reduction; Healthcare Information Systems; Image Processing; Image segmentation; Information Retrieval; Instance based learning; Machine Learning.Part II: ​Neural Network; Object Detection; Object Recognition; Online Handwriting Recognition; Optical Character Recognition; Security and Privacy; Unsupervised Clustering.

Advances In Computational Intelligence For Health Informatics And Computer Aided Diagnosis

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Author : A. Malini
language : en
Publisher: CRC Press
Release Date : 2025-04-23

Advances In Computational Intelligence For Health Informatics And Computer Aided Diagnosis written by A. Malini and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-23 with Medical categories.

This book provides a comprehensive overview of the intersection of computational intelligence, health informatics, and computer-aided diagnosis (CAD). The book explores and highlights the latest advancements, methodologies, applications, and tools in these fields. Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools covers a broad spectrum of computational intelligence approaches, from basic concepts to advanced methodologies. The focus on health informatics reflects the book's commitment to researching data integration, privacy issues, and interoperability issues that are crucial in today's healthcare landscape. The book's core is its in-depth examination of CAD systems, which encompasses numerous healthcare sectors and underlines the technological complexity involved in building accurate and efficient diagnostic tools. Some of the other key areas covered include: medical imaging analysis, disease identification and diagnosis, and drug research and development. It also provides case studies that demonstrate how computational intelligence methods are applied in real-world healthcare scenarios, giving readers a practical understanding of the subject matter. The authors then discuss future trends and directions in computational intelligence for health informatics. The book is designed to serve as a guide to for academics, professionals, and students who are curious about the challenges of integrating contemporary computational approaches into medical diagnostics and decision support.

Openmp Advanced Task Based Device And Compiler Programming

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Author : Simon McIntosh-Smith
language : en
Publisher: Springer Nature
Release Date : 2023-08-30

Openmp Advanced Task Based Device And Compiler Programming written by Simon McIntosh-Smith and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-30 with Computers categories.

This book constitutes the proceedings of the 19th International Workshop on OpenMP, IWOMP 2023, held in Bristol, UK, during September 13–15, 2023. The 15 full papers presented in this book were carefully reviewed and selected from 20 submissions. The papers are divided into the following topical sections: OpenMP and AI; Tasking Extensions; OpenMP Offload Experiences; Beyond Explicit GPU Support; and OpenMP Infrastructure and Evaluation.

Integrating Omics Data

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Author : George Tseng
language : en
Publisher: Cambridge University Press
Release Date : 2015-09-23

Integrating Omics Data written by George Tseng and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-23 with Mathematics categories.

Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.