Computational Intelligence In Machine Learning

Author : Srikanta Patnaik
Publisher : Springer Nature
ISBN 13 : 9811552436
Total Pages : 853 pages
Book Rating : 4.34/5 ( download)

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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.

Author : Priti Srinivas Sajja
Publisher : Springer Nature
ISBN 13 : 9811595895
Total Pages : 225 pages
Book Rating : 4.99/5 ( download)

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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.

Author : Rajshree Srivastava
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110649276
Total Pages : 414 pages
Book Rating : 4.77/5 ( download)

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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.

Author : Amit Kumar
Publisher : Springer Nature
ISBN 13 : 9811684847
Total Pages : 512 pages
Book Rating : 4.45/5 ( download)

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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.

Author : E. S. Gopi
Publisher : Springer Nature
ISBN 13 : 9811602891
Total Pages : 643 pages
Book Rating : 4.94/5 ( download)

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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.

Author : Stanley Cohen
Publisher : Elsevier Health Sciences
ISBN 13 : 0323675379
Total Pages : 290 pages
Book Rating : 4.76/5 ( download)

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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.

Author : Andreas Holzinger
Publisher : Springer Nature
ISBN 13 : 3030504026
Total Pages : 351 pages
Book Rating : 4.21/5 ( download)

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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.

Author : John Anderson
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.00/5 ( download)

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Download or read book Proceedings of the international conference on Machine Learning written by John Anderson and published by . This book was released on 19?? with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Amit Konar
Publisher : Springer Science & Business Media
ISBN 13 : 3540273352
Total Pages : 708 pages
Book Rating : 4.56/5 ( download)

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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.

Author : Mariya Ouaissa
Publisher : Springer Nature
ISBN 13 : 3030771857
Total Pages : 279 pages
Book Rating : 4.50/5 ( download)

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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.