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Normalization Techniques in Deep Learning (Synthesis Lectures on Computer Vision) - Tapa blanda

Huang, Lei

 
9783031145971: Normalization Techniques in Deep Learning (Synthesis Lectures on Computer Vision)
Tapa blanda
ISBN 10: 3031145976 ISBN 13: 9783031145971
Editorial: Springer, 2023

Sinopsis

​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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Acerca del 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.

De la contraportada

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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Editorial
Springer
Año de publicación
2023
Idioma
Inglés
ISBN 10 
3031145976
ISBN 13 
9783031145971
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
124
Contacto del fabricante
no disponible
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Otras ediciones populares con el mismo título

9783031145940: Normalization Techniques in Deep Learning (Synthesis Lectures on Computer Vision)

Edición Destacada

ISBN 10:  3031145941 ISBN 13:  9783031145940
Editorial: Springer International Publishin..., 2022
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