Development and analysis of deep learning architectures
Author(s)
Bibliographic Information
Development and analysis of deep learning architectures
（Studies in computational intelligence, v. 867）
Springer, c2020
Available at / 1 libraries
-
No Libraries matched.
- Remove all filters.
Note
Includes bibliographical references and index
Description and Table of Contents
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.
Table of Contents
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.
by "Nielsen BookData"
