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Normalization Techniques in Deep Learning

90,73 
90,73 
2025-07-31 90.7300 InStock
Nemokamas pristatymas į paštomatus per 18-22 darbo dienų užsakymams nuo 19,00 

Knygos aprašymas

¿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.

Informacija

Autorius: Lei Huang
Serija: Synthesis Lectures on Computer Vision
Leidėjas: Springer Nature Switzerland
Išleidimo metai: 2022
Knygos puslapių skaičius: 124
ISBN-10: 3031145941
ISBN-13: 9783031145940
Formatas: Knyga kietu viršeliu
Kalba: Anglų
Žanras: Mathematical modelling

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