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portada Normalization Techniques in Deep Learning
Type
Physical Book
Author
Publisher
Language
English
Pages
110
Format
Paperback
Dimensions
24.4x17x0.7 cm
Weight
0.21 kg.
ISBN13
9783031145971
Edition No.
1
Categories

Normalization Techniques in Deep Learning

Lei Huang (Author) · Springer · Paperback

Normalization Techniques in Deep Learning - Huang, Lei

New Book Imported to South Africa
Delivery: 21 Oct - 29 Oct Shipping: 6 to 7 business days.
R 1,366
R 1,366

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Synopsis "Normalization Techniques in Deep Learning"

​This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to specific tasks. Normalization methods can improve the training stability, optimization efficiency, and generalization ability of deep neural networks (DNNs) and have become basic components in most state-of-the-art DNN architectures. The author provides guidelines for elaborating, understanding, and applying normalization methods. This book is ideal for readers working on the development of novel deep learning algorithms and/or their applications to solve practical problems in computer vision and machine learning tasks. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs.

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