UID:
almahu_9948274957202882
Umfang:
XI, 292 p. 135 illus., 120 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2020.
ISBN:
9783030317645
Serie:
Studies in Computational Intelligence, 867
Inhalt:
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.
Anmerkung:
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.
In:
Springer eBooks
Weitere Ausg.:
Printed edition: ISBN 9783030317638
Weitere Ausg.:
Printed edition: ISBN 9783030317652
Weitere Ausg.:
Printed edition: ISBN 9783030317669
Sprache:
Englisch
DOI:
10.1007/978-3-030-31764-5
URL:
https://doi.org/10.1007/978-3-030-31764-5
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