Development and Analysis of Deep Learning Architectures
Published on 1. November 2019
XI, 292 pages
978-3-030-31764-5 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XI, 292 p. 135 illus., 120 illus. in color.
File size
13,17 MB
ISBN-13
978-3-030-31764-5 (9783030317645)
DOI
10.1007/978-3-030-31764-5
Schweitzer Classification
Other editions
Additional editions
Witold Pedrycz | Shyi-Ming Chen
Development and Analysis of Deep Learning Architectures
Book
11/2019
Springer
€171.19
Shipment within 7-9 days
Content
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.
