Normalization Techniques in Deep Learning, 2022nd Edition
- Hardcover
110 pages
- Release Date
9 October 2022
Summary
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 guid…
Book Details
| ISBN-13: | 9783031145940 |
|---|---|
| ISBN-10: | 3031145941 |
| Author: | Lei Huang |
| Publisher: | Springer International Publishing AG |
| Imprint: | Springer International Publishing AG |
| Format: | Hardcover |
| Number of Pages: | 110 |
| Edition: | 2022nd |
| Release Date: | 9 October 2022 |
| Weight: | 398g |
| Dimensions: | 240mm x 168mm |
| Series: | Synthesis Lectures on Computer Vision |
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About The Author
Lei Huang
Lei Huang, Ph.D., is an Associate Professor at Beihang University. His current research interests include normalization techniques involving methods, theories, and applications in training deep neural networks (DNNs). He also has wide interests in representation and optimization of deep learning theory and computer vision tasks. Dr. Huang serves as a reviewer for top-tier conferences and journals in machine learning and computer vision.
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