MatConvNet Deep Learning and IOS Mobile App Design for Pattern Recognition Emerging Research and Opportunities |
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| Author:
| Wu, Jiann-Ming
Tien, Chao-Yuan |
| Series title: | Advances in Computer and Electrical Engineering Ser. |
| ISBN: | 978-1-7998-1557-0 |
| Publication Date: | Apr 2020 |
| Publisher: | IGI Global
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| Imprint: | Engineering Science Reference |
| Book Format: | Digital download and online |
| List Price: | USD $195.00 |
Book Description:
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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...
More DescriptionDeep 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.