Normalization Techniques in Deep Learning - Synthesis Lectures on Computer Vision - Lei Huang - 图书 - Springer Nature Switzerland AG - 9783032199904 - 2026年6月12日
如封面与标题不符，以标题为准

Lei Huang
Normalization Techniques in Deep Learning - Synthesis Lectures on Computer Vision Second Edition 2026 edition

商品到货时接收邮件提醒
Do you have a profile? 登录

顾客评价：

根据欧洲消费者保护法享受14天退换货政策
Trustpilot平台高分认证
添加至iMusic心愿单

其他版本：

This book surveys normalization techniques with a deep analysis in training deep neural networks. 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. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs. This Second Edition builds upon the original material with the addition of more recent proposed methods and expanded technical details for new normalization methods and network architectures tailored to specific tasks.

介质类型 图书     Hardcover Book   (精装硬皮书)
已发行 2026年6月12日
ISBN13 9783032199904
出版商 Springer Nature Switzerland AG
页数 167
商品尺寸 150 × 220 × 20 mm   ·   369 g   (预估重量)

Mere med samme udgiver

查看Lei Huang的全部作品 ( 例如 Hardcover Book 及 Book )