Normalization Techniques in Deep Learning (1st ed. 2022) (Synthesis Lectures on Computer Vision)
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- Synopsis
- 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.
- Copyright:
- 2022
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783031145957
- Related ISBNs:
- 9783031145940
- Publisher:
- Springer International Publishing
- Date of Addition:
- 10/28/22
- Copyrighted By:
- The Editor
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Art and Architecture, Computers and Internet, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
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