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Machine Learning in Healthcare Informatics, Sumeet Dua; U. Rajendra Acharya; Prerna Dua


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Автор: Sumeet Dua; U. Rajendra Acharya; Prerna Dua
Название:  Machine Learning in Healthcare Informatics
ISBN: 9783662507636
Издательство: Springer
Классификация:
ISBN-10: 3662507633
Обложка/Формат: Paperback
Страницы: 332
Вес: 0.49 кг.
Дата издания: 03.09.2016
Серия: Intelligent Systems Reference Library
Язык: English
Размер: 234 x 156 x 18
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Providing a unique and integrated compendium of both current and emerging machine-learning paradigms in the vital field of health informatics, this work by leading experts reflects the diversity and complexity of this multi-disciplinary area of research.

Machine Learning in Healthcare Informatics

Автор: Sumeet Dua; U. Rajendra Acharya; Prerna Dua
Название: Machine Learning in Healthcare Informatics
ISBN: 3642400167 ISBN-13(EAN): 9783642400162
Издательство: Springer
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Цена: 139310.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Providing a unique and integrated compendium of both current and emerging machine-learning paradigms in the vital field of health informatics, this work by leading experts reflects the diversity and complexity of this multi-disciplinary area of research.

Artificial Neural Networks and Machine Learning – ICANN 2016

Автор: Villa
Название: Artificial Neural Networks and Machine Learning – ICANN 2016
ISBN: 3319447777 ISBN-13(EAN): 9783319447773
Издательство: Springer
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Цена: 68950.00 T
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Описание: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions.

Machine learning for adaptive many-core machines - a practical approach

Автор: Lopes, Noel Ribeiro, Bernardete
Название: Machine learning for adaptive many-core machines - a practical approach
ISBN: 3319069373 ISBN-13(EAN): 9783319069371
Издательство: Springer
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Цена: 130610.00 T
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Описание: Introduction.- Supervised Learning.- Unsupervised and Semi-supervised Learning.- Large-Scale Machine Learning.

Human Activity Recognition

Автор: Labrador, Miguel A.
Название: Human Activity Recognition
ISBN: 1466588276 ISBN-13(EAN): 9781466588271
Издательство: Taylor&Francis
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Цена: 137810.00 T
Наличие на складе: Невозможна поставка.
Описание:

Learn How to Design and Implement HAR Systems

The pervasiveness and range of capabilities of today's mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. Human Activity Recognition: Using Wearable Sensors and Smartphones focuses on the automatic identification of human activities from pervasive wearable sensors--a crucial component for health monitoring and also applicable to other areas, such as entertainment and tactical operations.

Developed from the authors' nearly four years of rigorous research in the field, the book covers the theory, fundamentals, and applications of human activity recognition (HAR). The authors examine how machine learning and pattern recognition tools help determine a user's activity during a certain period of time. They propose two systems for performing HAR: Centinela, an offline server-oriented HAR system, and Vigilante, a completely mobile real-time activity recognition system. The book also provides a practical guide to the development of activity recognition applications in the Android framework.


Machine Learning and Data Mining in Pattern Recognition

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319419196 ISBN-13(EAN): 9783319419190
Издательство: Springer
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Цена: 89440.00 T
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Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Artificial Neural Networks and Machine Learning – ICANN 2016

Автор: Villa
Название: Artificial Neural Networks and Machine Learning – ICANN 2016
ISBN: 3319447807 ISBN-13(EAN): 9783319447803
Издательство: Springer
Рейтинг:
Цена: 68950.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions.

Advances in Machine Learning

Автор: Zhi-Hua Zhou; Takashi Washio
Название: Advances in Machine Learning
ISBN: 3642052231 ISBN-13(EAN): 9783642052231
Издательство: Springer
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Цена: 83850.00 T
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Описание: Most submissions received four reviews, a few submissions received ?ve reviews, while only several submissions received three reviews.

Machine Learning for Cyber Physical Systems

Автор: J?rgen Beyerer; Oliver Niggemann; Christian K?hner
Название: Machine Learning for Cyber Physical Systems
ISBN: 3662538059 ISBN-13(EAN): 9783662538050
Издательство: Springer
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Цена: 158380.00 T
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Описание: The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, September 29th, 2016. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

Machine Learning in Medical Imaging

Автор: Wang
Название: Machine Learning in Medical Imaging
ISBN: 3319471562 ISBN-13(EAN): 9783319471563
Издательство: Springer
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Цена: 54040.00 T
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Описание: This book constitutes the refereed proceedings of the 7th International Workshop on Machine Learning in Medical Imaging, MLMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging.

Machine Learning and Intelligent Communications

Автор: Huang Xin-lin
Название: Machine Learning and Intelligent Communications
ISBN: 3319527290 ISBN-13(EAN): 9783319527291
Издательство: Springer
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Цена: 54040.00 T
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Описание:

Data mining in heterogeneous networks.- decentralized learning for wireless communication systems.- intelligent cooperative/distributed coding, intelligent cooperative networks.- iIntelligent massive MIMO, .- time coded multi-user MIMO system based on three dimensional complementary codes.- intelligent positioning and navigation systems.- intelligent spectrum allocation schemes.- machine learning algorithm &.- cognitive radio networks, machine learning for multimedia.


Augmented Cognition. Neurocognition and Machine Learning

Автор: Dylan D. Schmorrow; Cali M. Fidopiastis
Название: Augmented Cognition. Neurocognition and Machine Learning
ISBN: 3319586270 ISBN-13(EAN): 9783319586274
Издательство: Springer
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Цена: 74530.00 T
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Описание: This volume constitutes the proceedings of the 11th International Conference on Augmented Cognition, AC 2017, held as part of the International Conference on Human-Computer Interaction, HCII 2017, which took place in Vancouver, BC, Canada, in July 2017.

Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning

Автор: Thorsten Wuest
Название: Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
ISBN: 3319386980 ISBN-13(EAN): 9783319386980
Издательство: Springer
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Цена: 95770.00 T
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Описание: The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. In practice, this method can be used to identify the most important process parameters and state characteristics, the so-called state drivers, of a manufacturing system.


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