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Deep learning and parallel computing environment for bioengineering systems /, Sangiah, Arun Kumar,


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Цена: 21054.00р.
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При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Sangiah, Arun Kumar,   (Арун Кумар Сангья)
Название:  Deep learning and parallel computing environment for bioengineering systems /
Перевод названия: Арун Кумар Сангья: Среда глубокого обучения и параллельных вычислений для биоинженерных систем
ISBN: 9780128167182
Издательство: Elsevier Science
Классификация:




ISBN-10: 0128167181
Обложка/Формат: Paperback
Страницы: 320
Вес: 0.59 кг.
Дата издания: 01.08.2019
Язык: English
Размер: 194 x 235 x 14
Основная тема: Engineering / Electronics
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Европейский союз
Описание:

Deep Learning and Parallel Computing Environment for Bio-Engineering 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.

  • 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 todays intelligent data-centric critical systems and multi-media Cloud-Big data



High Performance Scientific Computing Using Distributed Infrastructures: Results And Scientific Applications Derived From The Italian Pon Recas Project

Автор: Merola Leonardo Et Al
Название: High Performance Scientific Computing Using Distributed Infrastructures: Results And Scientific Applications Derived From The Italian Pon Recas Project
ISBN: 9814759708 ISBN-13(EAN): 9789814759700
Издательство: World Scientific Publishing
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Цена: 25978.00 р.
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Описание:

This book aims to provide a deep look into Italian actions taken in some fields of science and high performance computing (HPC), and the Italian effort to bridge the HPC gap with respect to Europe. The Italian PON ReCaS Project is written for graduate readers and professionals in the field of high performance computing. It presents and discusses innovative and important technological solutions, and describes interesting results in various fields of application.

ReCaS stands for "Rete di Calcolo per SuperB e altre applicazioni" and is a computing network infrastructure in Southern Italy devoted to scientific and non-scientific applications within the vision of a common European infrastructure for computing, storage and network. The ReCaS project is part of the 2007-2013 European Union strategy, and was funded by the Italian Ministry of Research and Education (MIUR) for the development and enhancement of a distributed computing infrastructure of the Grid/Cloud type over the four EU 'Convergence' regions in Southern Italy: Campania, Puglia and Sicily and Calabria.

The network will be open and accessible to all researchers, public and private, and will be characterized by unprecedented computing power and storage capacity. Posted in the European Grid Infrastructure EGI, ReCaS is also an opportunity to the countries of the Mediterranean area and extends the potential of the current network.


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