Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances (Studies in Computational Intelligence, 1070) - Hardcover

Sun, Yanan; Yen, Gary G.; Zhang, Mengjie

Hardcover

ISBN 10: 3031168674 ISBN 13: 9783031168673

Publisher: Springer, 2022

Synopsis

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.

About this title

From the Back Cover

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.

Edition details

• Publisher: Springer
• Publication date: 2022
• Language: English
• ISBN 10: 3031168674
• ISBN 13: 9783031168673
• Binding: Hardcover
• Edition number: 1
• Number of pages: 347