Normalization Techniques in Deep Learning
暫譯: 深度學習中的正規化技術

Name: Normalization Techniques in Deep Learning
Price: 1833 TWD
Availability: OnlineOnly
Author: Huang, Lei
ISBN: 3032199905

Huang, Lei

出版商: Springer
出版日期: 2026-07-14
售價: $1,930
貴賓價: 9.5 折 $1,833
語言: 英文
頁數: 167
裝訂: Hardcover - also called cloth, retail trade, or trade
ISBN: 3032199905
ISBN-13: 9783032199904
相關分類: DeepLearning

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商品描述

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.

商品描述(中文翻譯)

本書調查了正規化技術，並深入分析了訓練深度神經網絡。正規化方法可以提高深度神經網絡（DNNs）的訓練穩定性、優化效率和泛化能力，並已成為大多數最先進的DNN架構中的基本組件。作者提供了闡述、理解和應用正規化方法的指導方針。本書非常適合從事新穎深度學習算法開發和/或其在計算機視覺和機器學習中解決實際問題應用的讀者。該書也為新進研究人員、工程師和學生提供資源，幫助他們理解和訓練DNN。本第二版在原有材料的基礎上，增加了最近提出的方法和針對特定任務的新正規化方法及網絡架構的擴展技術細節。

作者簡介

Lei Huang, Ph.D., is an Associate Professor and Doctoral Supervisor in the School of Artificial Intelligence (Institute) at Beihang University, China. His current research mainly focuses on normalization techniques (involving methods, theories, and applications) in training DNNs. He also has wide interests in deep learning theory (representation and optimization) and computer vision tasks. Dr. Huang has published over 40 peer-reviewed articles in top-tier machine learning and computer vision conferences and journals such as CVPR, NeurIPS, ICML, and IEEE TPAMI. He serves in program committees and as a reviewer for the top-tier conferences and journals in machine learning and computer vision. Dr. Huang received his B.Sc. and Ph.D. degrees from Beihang University.

作者簡介(中文翻譯)

雷黃博士是中國北京航空航天大學人工智慧學院（研究所）的副教授及博士生導師。他目前的研究主要集中在訓練深度神經網絡（DNNs）中的正規化技術（包括方法、理論和應用）。他對深度學習理論（表示法和優化）以及計算機視覺任務也有廣泛的興趣。黃博士在頂尖的機器學習和計算機視覺會議及期刊上發表了超過40篇經過同行評審的文章，如CVPR、NeurIPS、ICML和IEEE TPAMI。他在機器學習和計算機視覺的頂尖會議和期刊中擔任程序委員會成員及審稿人。黃博士獲得了北京航空航天大學的學士和博士學位。