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MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities, Wu Jiann-Ming, Tien Chao-Yuan


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Автор: Wu Jiann-Ming, Tien Chao-Yuan
Название:  MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities
ISBN: 9781799815549
Издательство: Mare Nostrum (Eurospan)
Классификация:
ISBN-10: 1799815544
Обложка/Формат: Hardcover
Страницы: 212
Вес: 0.58 кг.
Дата издания: 10.04.2020
Язык: English
Иллюстрации: Illustrations, unspecified
Размер: 25.40 x 17.78 x 1.27 cm
Читательская аудитория: Tertiary education (us: college)
Подзаголовок: Emerging research and opportunities
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Поставляется из: Англии
Описание: Deep learning has become a trending area of research due to its adaptive characteristics and high levels of applicability. In recent years, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image classification. As these technologies continue to advance, professionals have begun translating this intelligent programming language into mobile applications for devices. Programmers and web developers are in need of significant research on how to successfully develop pattern recognition applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities is an essential reference source that presents a solution to developing intelligent pattern recognition Apps on iOS devices based on MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification, this book is ideally designed for programmers, developers, researchers, practitioners, engineers, academicians, students, scientists, and educators seeking coverage on the specific development of iOS mobile applications using pattern recognition strategies.


Reproducible Research in Pattern Recognition

Автор: Bertrand Kerautret; Miguel Colom; Pascal Monasse
Название: Reproducible Research in Pattern Recognition
ISBN: 3319564137 ISBN-13(EAN): 9783319564135
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Reproducible Research in Pattern Recognition, RRPR 2016, held in Cancun, Mexico, in December 2016. The 12 revised full papers, among them 2 invited talks, presented were carefully reviewed and selected from 16 submissions.

Design, Implementation, and Analysis of Next Generation Optical Networks: Emerging Research and Opportunities

Автор: Imtiaz Waqas Ahmed, Rуka Rastislav
Название: Design, Implementation, and Analysis of Next Generation Optical Networks: Emerging Research and Opportunities
ISBN: 1522597689 ISBN-13(EAN): 9781522597681
Издательство: Mare Nostrum (Eurospan)
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Цена: 18810.00 р.
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Описание: Discusses the next generation of high capacity passive optical access networks in terms of design, implementation, and analysis and offers a complete reference of technology solutions for next-generation optical networks. The book features research on topics such as artificial intelligence, electromagnetic interface, and wireless communication.

Reproducible Research in Pattern Recognition

Автор: Bertrand Kerautret; Miguel Colom; Daniel Lopresti;
Название: Reproducible Research in Pattern Recognition
ISBN: 3030239861 ISBN-13(EAN): 9783030239862
Издательство: Springer
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Цена: 6986.00 р.
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Описание:

This book constitutes the thoroughly refereed post-workshop proceedings of the Second International Workshop on Reproducible Research in Pattern Recognition, RRPR 2018, in Beijing, China in August 2018.
The 8 revised full papers, presented together 6 short papers, were carefully reviewed and selected from 14 submissions. This year the workshop did focus on Digital Geometry and Mathematical Morphology.
The first track 1 on RR Framework was dedicated to the general topics of Reproducible Research in Computer Science
with a potential link to Image Processing and Pattern Recognition. In the second track 2 the authors described their works in terms of Reproducible Research.

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