Ji Liu – författare

Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and other applications by presenting neural network algorithms and hardware design optimization approaches for Edge-deep learning. Applications are introduced in each section, and a comprehensive example, smart surveillance cameras, is presented at the end of the book, integrating innovation in both algorithm and hardware architecture. Structured into three parts, the book covers core concepts, theories and algorithms and architecture optimization.This book provides a solution for researchers looking to maximize the performance of deep learning models on Edge-computing devices through algorithm-hardware co-design. Focuses on hardware architecture and embedded deep learning, including neural networks Brings together neural network algorithm and hardware design optimization approaches to deep learning, alongside real-world applications Considers how Edge computing solves privacy, latency and power consumption concerns related to the use of the Cloud Describes how to maximize the performance of deep learning on Edge-computing devices Presents the latest research on neural network compression coding, deep learning algorithms, chip co-design and intelligent monitoring

This book sets out to examine the underlying educational implications of rapid economic transformation, using illustrative analyses of teacher labour markets during the years of unprecedented economic growth in China.Combining historic document archive and empirical micro-level quantitative data, the book examines trends in teacher labour market and their relevant consequences by investigating wage-attractiveness of the teaching profession, consequential shifts in the composition of the teacher force, implications for student learning, and emerging alternative career destinations for teacher exits. While this book focuses on a specific country case, its analytic context is broadly relevant for a range of developing countries that aspire to better understand, through an occupational choice lens, how shifting economic landscapes influence teacher career decisions and consequentially teacher quality and student learning.Teacher policy scholars, comparative education researchers, labour economists, economic and education historians, teacher union researchers, and education policy makers will find this volume of interest.

This book sets out to examine the underlying educational implications of rapid economic transformation, using illustrative analyses of teacher labour markets during the years of unprecedented economic growth in China.Combining historic document archive and empirical micro-level quantitative data, the book examines trends in teacher labour market and their relevant consequences by investigating wage-attractiveness of the teaching profession, consequential shifts in the composition of the teacher force, implications for student learning, and emerging alternative career destinations for teacher exits. While this book focuses on a specific country case, its analytic context is broadly relevant for a range of developing countries that aspire to better understand, through an occupational choice lens, how shifting economic landscapes influence teacher career decisions and consequentially teacher quality and student learning.Teacher policy scholars, comparative education researchers, labour economists, economic and education historians, teacher union researchers, and education policy makers will find this volume of interest.