Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances (Hardcover, 1st ed. 2023)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 1070
Release date:	November 2022
First published:	2023
Authors:	Yanan Sun • Gary G. Yen • Mengjie Zhang
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	331
Edition:	1st ed. 2023
ISBN-13:	978-3-03-116867-3
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-03-116867-4
Barcode:	9783031168673

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