Computational Intelligence In Machine Learning
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| Author | : Priti Srinivas Sajja |
| Publisher | : Springer Nature |
| Total Pages | : 225 |
| Release | : 2020-11-16 |
| Genre | : Technology & Engineering |
| ISBN | : 9811595895 |
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 |
| Total Pages | : 346 |
| Release | : 2020-06-22 |
| Genre | : Computers |
| ISBN | : 3110648199 |
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 | : Jyotsna Kumar Mandal |
| Publisher | : Springer Nature |
| Total Pages | : 201 |
| Release | : 2020-11-24 |
| Genre | : Technology & Engineering |
| ISBN | : 9811586101 |
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.
| Author | : Stanley Cohen |
| Publisher | : Elsevier Health Sciences |
| Total Pages | : 290 |
| Release | : 2020-06-02 |
| Genre | : Medical |
| ISBN | : 0323675379 |
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 | : Amit Kumar |
| Publisher | : Springer Nature |
| Total Pages | : 512 |
| Release | : 2022-03-03 |
| Genre | : Technology & Engineering |
| ISBN | : 9811684847 |
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 | : Srikanta Patnaik |
| Publisher | : Springer Nature |
| Total Pages | : 853 |
| Release | : 2020-07-25 |
| Genre | : Technology & Engineering |
| ISBN | : 9811552436 |
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 | : Rudolf Kruse |
| Publisher | : Springer |
| Total Pages | : 556 |
| Release | : 2016-09-16 |
| Genre | : Computers |
| ISBN | : 1447172965 |
This textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced second edition has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs. Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.
| Author | : Tero Tuovinen |
| Publisher | : Springer Nature |
| Total Pages | : 278 |
| Release | : 2021-08-19 |
| Genre | : Technology & Engineering |
| ISBN | : 3030707873 |
This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors.
| Author | : David I. Poole |
| Publisher | : Oxford University Press on Demand |
| Total Pages | : 558 |
| Release | : 1998 |
| Genre | : Computers |
| ISBN | : 9780195102703 |
Provides an integrated introduction to artificial intelligence. Develops AI representation schemes and describes their uses for diverse applications, from autonomous robots to diagnostic assistants to infobots. DLC: Artificial intelligence.
| Author | : Andreas Holzinger |
| Publisher | : Springer Nature |
| Total Pages | : 351 |
| Release | : 2020-06-24 |
| Genre | : Computers |
| ISBN | : 3030504026 |
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.
