Pedrycz / Chen Development and Analysis of Deep Learning Architectures

Erscheinungsjahr 2019
ISBN: 978-3-030-31764-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 867, 292 Seiten, eBook

Reihe: Studies in Computational Intelligence

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.

Zielgruppe

Research

Autoren/Hrsg.

Pedrycz, Witold

Chen, Shyi-Ming

Inhaltsverzeichnis

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.