Название: Deep Learning and Parallel Computing Environment for Bioengineering Systems Автор: Arun Kumar Sangaiah
Издательство: Academic Press
Год: 2019
Страниц: 269
Язык: английский
Формат: pdf (true)
Размер: 24.7 MB
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas.
Deep Machine Learning is an emergent area in the field of computational intelligence (CI) research that is concerned with the analysis and design of learning algorithms, representations of data, at multiple levels of abstraction. Deep learning is a technique for implementing machine learning that provides an effective solution for parallel computing environment in bioengineering problems. It encompasses artificial intelligence (AI), artificial neural network, reasoning, natural language processing that will be helpful to human intelligence and decision making process.
Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems
Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems
Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data
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