Computational Intelligence and Machine Learning

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Publisher : Springer Nature
ISBN 13 : 9811586101
Total Pages : 201 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Computational Intelligence and Machine Learning by : Jyotsna Kumar Mandal

Download or read book Computational Intelligence and Machine Learning written by Jyotsna Kumar Mandal and published by Springer Nature. This book was released on 2020-11-24 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on both theory and applications in the broad areas of computational intelligence and machine learning. The proceedings of the Seventh International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019) present research papers in the areas of advanced computing, networking, and informatics. It brings together contributions from scientists, professors, scholars, and students and presents essential information on the topic. It also discusses the practical challenges encountered and the solutions used to overcome them, the goal being to promote the “translation” of basic research into applied research and of applied research into practice. The works presented here also demonstrate the importance of basic scientific research in a range of fields.

Advances in Machine Learning and Computational Intelligence

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Publisher : Springer Nature
ISBN 13 : 9811552436
Total Pages : 853 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Advances in Machine Learning and Computational Intelligence by : Srikanta Patnaik

Download or read book Advances in Machine Learning and Computational Intelligence written by Srikanta Patnaik and published by Springer Nature. This book was released on 2020-07-25 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-quality papers presented at the International Conference on Machine Learning and Computational Intelligence (ICMLCI-2019), jointly organized by Kunming University of Science and Technology and the Interscience Research Network, Bhubaneswar, India, from April 6 to 7, 2019. Addressing virtually all aspects of intelligent systems, soft computing and machine learning, the topics covered include: prediction; data mining; information retrieval; game playing; robotics; learning methods; pattern visualization; automated knowledge acquisition; fuzzy, stochastic and probabilistic computing; neural computing; big data; social networks and applications of soft computing in various areas.

Computational Intelligence for Machine Learning and Healthcare Informatics

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110649276
Total Pages : 414 pages
Book Rating : 4.1/5 (16 download)

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Book Synopsis Computational Intelligence for Machine Learning and Healthcare Informatics by : Rajshree Srivastava

Download or read book Computational Intelligence for Machine Learning and Healthcare Informatics written by Rajshree Srivastava and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-06-22 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Illustrated Computational Intelligence

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Publisher : Springer Nature
ISBN 13 : 9811595895
Total Pages : 225 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Illustrated Computational Intelligence by : Priti Srinivas Sajja

Download or read book Illustrated Computational Intelligence written by Priti Srinivas Sajja and published by Springer Nature. This book was released on 2020-11-16 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a summary of artificial intelligence and machine learning techniques in its first two chapters. The remaining chapters of the book provide everything one must know about the basic artificial intelligence to modern machine intelligence techniques including the hybrid computational intelligence technique, using the concepts of several real-life solved examples, design of projects and research ideas. The solved examples with more than 200 illustrations presented in the book are a great help to instructors, students, non–AI professionals, and researchers. Each example is discussed in detail with encoding, normalization, architecture, detailed design, process flow, and sample input/output. Summary of the fundamental concepts with solved examples is a unique combination and highlight of this book.

Artificial Intelligence and Machine Learning for COVID-19

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Publisher : Springer Nature
ISBN 13 : 3030601889
Total Pages : 266 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Artificial Intelligence and Machine Learning for COVID-19 by : Fadi Al-Turjman

Download or read book Artificial Intelligence and Machine Learning for COVID-19 written by Fadi Al-Turjman and published by Springer Nature. This book was released on 2021-02-19 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies.

Artificial Intelligence and Deep Learning in Pathology

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Publisher : Elsevier Health Sciences
ISBN 13 : 0323675379
Total Pages : 290 pages
Book Rating : 4.3/5 (236 download)

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Book Synopsis Artificial Intelligence and Deep Learning in Pathology by : Stanley Cohen

Download or read book Artificial Intelligence and Deep Learning in Pathology written by Stanley Cohen and published by Elsevier Health Sciences. This book was released on 2020-06-02 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.

Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

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Publisher : Springer Nature
ISBN 13 : 9811602891
Total Pages : 643 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication by : E. S. Gopi

Download or read book Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication written by E. S. Gopi and published by Springer Nature. This book was released on 2021-05-28 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of best selected research papers presented at the Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2020) held during October 22nd to 24th 2020, at the Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli, India. The presented papers are grouped under the following topics (a) Machine Learning, Deep learning and Computational intelligence algorithms (b)Wireless communication systems and (c) Mobile data applications and are included in the book. The topics include the latest research and results in the areas of network prediction, traffic classification, call detail record mining, mobile health care, mobile pattern recognition, natural language processing, automatic speech processing, mobility analysis, indoor localization, wireless sensor networks (WSN), energy minimization, routing, scheduling, resource allocation, multiple access, power control, malware detection, cyber security, flooding attacks detection, mobile apps sniffing, MIMO detection, signal detection in MIMO-OFDM, modulation recognition, channel estimation, MIMO nonlinear equalization, super-resolution channel and direction-of-arrival estimation. The book is a rich reference material for academia and industry.

Machine Learning and Artificial Intelligence

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Publisher : Springer Nature
ISBN 13 : 3030266222
Total Pages : 261 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Machine Learning and Artificial Intelligence by : Ameet V Joshi

Download or read book Machine Learning and Artificial Intelligence written by Ameet V Joshi and published by Springer Nature. This book was released on 2019-09-24 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible. Presents a full reference to artificial intelligence and machine learning techniques - in theory and application; Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible; Connects all ML and AI techniques to applications and introduces implementations.

Computational Intelligence in Machine Learning

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Publisher : Springer Nature
ISBN 13 : 9811684847
Total Pages : 512 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Computational Intelligence in Machine Learning by : Amit Kumar

Download or read book Computational Intelligence in Machine Learning written by Amit Kumar and published by Springer Nature. This book was released on 2022-03-03 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book includes select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2021). The book constitutes peer-reviewed papers on machine learning, computational intelligence, the internet of things, and smart city applications emphasizing multi-disciplinary research in artificial intelligence and cyber-physical systems. This book addresses the comprehensive nature of computational intelligence, artificial intelligence, machine learning, and deep learning to emphasize its character in modeling, identification, optimization, prediction, forecasting, and control of future intelligent systems. The book will be useful for researchers, research scholars, and students to formulate their research ideas and find future directions in these areas. It will help the readers to solve a diverse range of problems in industries and their real-world applications.

Artificial Intelligence and Machine Learning for Digital Pathology

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Publisher : Springer Nature
ISBN 13 : 3030504026
Total Pages : 351 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Artificial Intelligence and Machine Learning for Digital Pathology by : Andreas Holzinger

Download or read book Artificial Intelligence and Machine Learning for Digital Pathology written by Andreas Holzinger and published by Springer Nature. This book was released on 2020-06-24 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions.

Artificial Intelligence and Machine Learning in Public Healthcare

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Publisher : Springer Nature
ISBN 13 : 9811667683
Total Pages : 93 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Artificial Intelligence and Machine Learning in Public Healthcare by : KC Santosh

Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh and published by Springer Nature. This book was released on 2022-01-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Computational Intelligence in Recent Communication Networks

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Publisher : Springer Nature
ISBN 13 : 3030771857
Total Pages : 279 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Computational Intelligence in Recent Communication Networks by : Mariya Ouaissa

Download or read book Computational Intelligence in Recent Communication Networks written by Mariya Ouaissa and published by Springer Nature. This book was released on 2022-02-21 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the use of Artificial Intelligence and Machine Learning (AI/ML) based techniques to solve issues related to communication networks, their layers, as well as their applications. The book first offers an introduction to recent trends regarding communication networks. The authors then provide an overview of theoretical concepts of AI/ML, techniques and protocols used in different layers of communication. Furthermore, this book presents solutions that help analyze complex patterns in user data and ultimately improve productivity. Throughout, AI/ML-based solutions are provided, for topics such as signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction, software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The book features chapters from a large spectrum of authors including researchers, students, as well as industrials involved in research and development.

Machine Learning and Artificial Intelligence

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Publisher : IOS Press
ISBN 13 : 1643681370
Total Pages : 482 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis Machine Learning and Artificial Intelligence by : A.J. Tallón-Ballesteros

Download or read book Machine Learning and Artificial Intelligence written by A.J. Tallón-Ballesteros and published by IOS Press. This book was released on 2020-12-15 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning and artificial intelligence are already widely applied to facilitate our daily lives, as well as scientific research, but with the world currently facing a global COVID-19 pandemic, their capacity to provide an important tool to support those searching for a way to combat the novel corona virus has never been more important. This book presents the proceedings of the International Conference on Machine Learning and Intelligent Systems (MLIS 2020), which was due to be held in Seoul, Korea, from 25-28 October 2020, but which was delivered as an online conference on the same dates due to COVID-19 restrictions. MLIS 2020 was the latest in a series of annual conferences that aim to provide a platform for exchanging knowledge about the most recent scientific and technological advances in the field of machine learning and intelligent systems. The annual conference also strengthens links within the scientific community in related research areas. The book contains 53 papers, selected from more than 160 submissions and presented at MLIS 2020. Selection was based on the results of review and scored on: originality, scientific/practical significance, compelling logical reasoning and language. Topics covered include: data mining, image processing, neural networks, human health, natural language processing, video processing, computational intelligence, expert systems, human-computer interaction, deep learning, and robotics. Offering a current overview of research and developments in machine learning and artificial intelligence, the book will be of interest to all those working in the field.

Machine Learning in Document Analysis and Recognition

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Publisher : Springer Science & Business Media
ISBN 13 : 3540762795
Total Pages : 435 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Machine Learning in Document Analysis and Recognition by : Simone Marinai

Download or read book Machine Learning in Document Analysis and Recognition written by Simone Marinai and published by Springer Science & Business Media. This book was released on 2008-01-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and state-of-the-art reviews by leading researchers all over the world. It includes pointers to challenges and opportunities for future research directions. The main goal of the book is to identify good practices for the use of learning strategies in DAR.

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

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Publisher : CRC Press
ISBN 13 : 1000179532
Total Pages : 255 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches by : K. Gayathri Devi

Download or read book Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches written by K. Gayathri Devi and published by CRC Press. This book was released on 2020-10-08 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning

Computational Intelligence

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Publisher : Springer Science & Business Media
ISBN 13 : 3540273352
Total Pages : 708 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Computational Intelligence by : Amit Konar

Download or read book Computational Intelligence written by Amit Konar and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence: Principles, Techniques and Applications presents both theories and applications of computational intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects of fuzzy sets and logic, neural networks, evolutionary computing and belief networks. The application areas include fuzzy databases, fuzzy control, image understanding, expert systems, object recognition, criminal investigation, telecommunication networks, and intelligent robots. The book contains many numerical examples and homework problems with sufficient hints so that the students can solve them on their own.

Combating Fake News with Computational Intelligence Techniques

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Publisher : Springer Nature
ISBN 13 : 3030900878
Total Pages : 432 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Combating Fake News with Computational Intelligence Techniques by : Mohamed Lahby

Download or read book Combating Fake News with Computational Intelligence Techniques written by Mohamed Lahby and published by Springer Nature. This book was released on 2021-12-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest cutting-edge research, theoretical methods, and novel applications in the field of computational intelligence techniques and methods for combating fake news. Fake news is everywhere. Despite the efforts of major social network players such as Facebook and Twitter to fight disinformation, miracle cures and conspiracy theories continue to rain down on the net. Artificial intelligence can be a bulwark against the diversity of fake news on the Internet and social networks. This book discusses new models, practical solutions, and technological advances related to detecting and analyzing fake news based on computational intelligence models and techniques, to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence techniques. Further, the book helps readers understand computational intelligence techniques combating fake news in a systematic and straightforward way.