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Normalization Techniques in Deep Learning - Lei Huang

angļu valoda
2023-10-10
63,51 € 90,73 €

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¿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 beco ... Pilns apraksts

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¿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.

Vairāk informācijas

Autors Lei Huang
Izdevējs Springer Nature Switzerland
Series Synthesis Lectures on Computer Vision
Izlaides gads 2023
Vāka tips Mīkstais vāks
EAN 9783031145971
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63,51 € 90,73 €