MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities

MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities
Author :
Publisher : IGI Global
Total Pages : 181
Release :
ISBN-10 : 9781799815563
ISBN-13 : 1799815560
Rating : 4/5 (560 Downloads)

Book Synopsis MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities by : Wu, Jiann-Ming

Download or read book MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities written by Wu, Jiann-Ming and published by IGI Global. This book was released on 2020-04-17 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities Related Books

MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities
Language: en
Pages: 181
Authors: Wu, Jiann-Ming
Categories: Computers
Type: BOOK - Published: 2020-04-17 - Publisher: IGI Global

DOWNLOAD EBOOK

Deep learning has become a trending area of research due to its adaptive characteristics and high levels of applicability. In recent years, researchers have beg
Industrial Internet of Things and Cyber-Physical Systems: Transforming the Conventional to Digital
Language: en
Pages: 431
Authors: Kumar, Pardeep
Categories: Computers
Type: BOOK - Published: 2020-05-22 - Publisher: IGI Global

DOWNLOAD EBOOK

With the help of artificial intelligence, machine learning, and big data analytics, the internet of things (IoT) is creating partnerships within industry where
Handbook of Research on Engineering Innovations and Technology Management in Organizations
Language: en
Pages: 459
Authors: Gaur, Loveleen
Categories: Technology & Engineering
Type: BOOK - Published: 2020-04-17 - Publisher: IGI Global

DOWNLOAD EBOOK

As technology weaves itself more tightly into everyday life, socio-economic development has become intricately tied to these ever-evolving innovations. Technolo
Deep Learning for Computer Vision
Language: en
Pages: 564
Authors: Jason Brownlee
Categories: Computers
Type: BOOK - Published: 2019-04-04 - Publisher: Machine Learning Mastery

DOWNLOAD EBOOK

Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Evolutionary Computing and Mobile Sustainable Networks
Language: en
Pages: 975
Authors: V. Suma
Categories: Technology & Engineering
Type: BOOK - Published: 2020-07-31 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book features selected research papers presented at the International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN 2020),