Normalization Techniques in Deep Learning
Aus der Reihe
Synthesis Lectures on Computer Vision
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- Taschenbuch ausgewählt
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Sprache:Englisch
Fr. 79.90
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Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
10.10.2023
Abbildungen
XI, 110 p. 26 illus., 21 illus. in color.
Verlag
SpringerSeitenzahl
110
Maße (L/B/H)
24/16.8/0.8 cm
Gewicht
223 g
Auflage
23001 Auflage 1st ed. 2022
Sprache
Englisch
ISBN
978-3-031-14597-1
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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