Bøker av Lei Huang

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.

Nowadays most studies to elucidate the mechanisms of sediment transport have concentrated on physical-chemical sediment properties, little work explicitly coupled sediment dynamics and the environmental effects under the influence of micro-ecosystem, thus leaving a serious gap in water and sediment sciences as well as water ecological research.