Development and Analysis of Deep Learning Architectures

Witold Pedrycz, Shyi-Ming Chen (Herausgeber)

Buch | Softcover

XI, 292 Seiten

2020
Springer International Publishing (Verlag)
978-3-030-31766-9 (ISBN)

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This book offers a timely reflection on the remarkable range of algorithms and applications that have made the area of deep learning so attractive and heavily researched today. Introducing the diversity of learning mechanisms in the environment of big data, and presenting authoritative studies in fields such as sensor design, health care, autonomous driving, industrial control and wireless communication, it enables readers to gain a practical understanding of design. The book also discusses systematic design procedures, optimization techniques, and validation processes.

Preface.- Chapter 1. Direct Error Driven Learning for Classification in Applications Generating Big-Data.- Chapter 2. Deep Learning for Soft Sensor Design.- Chapter 3. Case Study: Deep Convolutional Networks in Healthcare, etc.

Erscheinungsdatum	14.11.2020
Reihe/Serie	Studies in Computational Intelligence
Zusatzinfo	XI, 292 p. 135 illus., 120 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	468 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Technik
Schlagworte	AI • Computational Intelligence • computer vision • Deep Learning Architectures • Development Paradigms • Image Processing • Knowledge Representation • machine learning • Natural Language Processing • pattern recognition
ISBN-10	3-030-31766-8 / 3030317668
ISBN-13	978-3-030-31766-9 / 9783030317669
Zustand	Neuware