Development and Analysis of Deep Learning Architectures (eBook, PDF)

Redaktion: Pedrycz, Witold; Chen, Shyi-Ming

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer-Verlag GmbH
• Seitenzahl: 292
• Erscheinungstermin: 1. November 2019
• Englisch
• ISBN-13: 9783030317645
• Artikelnr.: 58045783

Inhaltsangabe

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.