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

MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition

Emerging Research and Opportunities
Buch | Softcover
181 Seiten
2020
Business Science Reference (Verlag)
978-1-7998-1555-6 (ISBN)
247,10 inkl. MwSt
Presents a solution to developing intelligent pattern recognition Apps on iOS devices based on MatConvNet deep learning. The book presents research on a range of topics, including medical image diagnosis, convolutional neural networks, and character classification.
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.
Erscheinungsdatum
Sprache englisch
Maße 178 x 254 mm
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 1-7998-1555-2 / 1799815552
ISBN-13 978-1-7998-1555-6 / 9781799815556
Zustand Neuware
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