Overview
- Introduces the fundamentals and up-to-date methods of evolutionary deep neural architecture search
- Provides the target readers with sufficient details learning from scratch
- Inspires the students to develop more effective and efficient EDNAS methods
Part of the book series: Studies in Computational Intelligence (SCI, volume 1070)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (17 chapters)
-
Front Matter
-
Fundamentals and Backgrounds
-
Front Matter
-
-
Evolutionary Deep Neural Architecture Search for Unsupervised DNNs
-
Front Matter
-
-
Evolutionary Deep Neural Architecture Search for Supervised DNNs
-
Front Matter
-
-
Recent Advances in Evolutionary Deep Neural Architecture Search
-
Front Matter
-
Keywords
About this book
This book systematically narrates the fundamentals, methods, and recent advances of evolutionary deep neural architecture search chapter by chapter. This will provide the target readers with sufficient details learning from scratch. In particular, the method parts are devoted to the architecture search of unsupervised and supervised deep neural networks. The people, who would like to use deep neural networks but have no/limited expertise in manually designing the optimal deep architectures, will be the main audience. This may include the researchers who focus on developing novel evolutionary deep architecture search methods for general tasks, the students who would like to study the knowledge related to evolutionary deep neural architecture search and perform related research in the future, and the practitioners from the fields of computer vision, natural language processing, and others where the deep neural networks have been successfully and largely used in their respective fields.
Authors and Affiliations
Bibliographic Information
Book Title: Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances
Authors: Yanan Sun, Gary G. Yen, Mengjie Zhang
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-031-16868-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-16867-3Published: 09 November 2022
Softcover ISBN: 978-3-031-16870-3Published: 10 November 2023
eBook ISBN: 978-3-031-16868-0Published: 08 November 2022
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 331
Number of Illustrations: 14 b/w illustrations, 77 illustrations in colour