Normalization Techniques in Deep Learning

Name: Normalization Techniques in Deep Learning
Brand: Lei Huang
SKU: 424533881
Price: 47.07 EUR
Availability: InStock

von Lei Huang Verlag: Springer International Publishing,

Erschienen 2023.

42453388/1

Weight Normalization, Computer Vision, Optimization, Image Style Transfer, Deep Neural Networks (DNNs), Domain Adaptation, Generative Adversarial Networks, Artificial Intelligence, Machine Learning, Normalization Techniques, Batch Normalization, Statistical Learning, Image Classifcation, Natural Language Processing (NLP)

Produktart:: 📚 Bücher
Autor(en):: Huang, Lei:
Anbieter:: Buchpark GmbH
Bestell-Nr.:: 424533881
Katalog:: Varia
ISBN | EAN:: 3031145976 | 9783031145971
Stichworte:: Weight, Normalization, Computer, Vision, Optimization, Image, Style, Transfer, Deep, Neural, Networks, (DNNs), Domain, Adaptation, Generative, Adversarial, Artificial, Intelligence, Machine, Learning, Techniques, Batch, Statistical, Classifcation, Natural, Language, Processing, (NLP)…
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Verlagstext

¿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.

Über den Autor

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.