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Normalization Techniques in Deep Learning

Language EnglishEnglish
Book Hardback
Book Normalization Techniques in Deep Learning Lei Huang
Libristo code: 39467705
Publishers Springer, Berlin, November 2021
This book presents and surveys normalization techniques with a deep analysis in training deep neural... Full description
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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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About the book

Full name Normalization Techniques in Deep Learning
Author Lei Huang
Language English
Binding Book - Hardback
Date of issue 2022
Number of pages 110
EAN 9783031145940
Libristo code 39467705
Publishers Springer, Berlin
Weight 398
Dimensions 168 x 240 x 13
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