Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture

ISBN-13: 9780323857833 / Angielski / Miękka / 2022 / 200 str.

Xichuan Zhou; Ji Liu; Cong Shi

Spis treści

Part 1. Introduction
1. Introduction
 
Part 2. Theory and Algorithm
2. Model Inference on Edge Device
3. Model Training on Edge Device
4. Network Encoding and Quantization
 
Part 3. Architecture Optimization
5. DANoC: An Algorithm and Hardware Codesign Prototype
6. Ensemble Spiking Networks on Edge Device
7. SenseCamera: A Learning Based Multifunctional Smart Camera Prototype

O autorze

Xichuan Zhou is Professor and Vice Dean in the School of Microelectronics and Communication Engineering, at Chongqing University, China. He received his PhD from Zhejiang University. His research focuses on embedded neural computing, brain-like sensing, and pervasive computing. He has won professional awards for his work, and has published over 50 papers. Research Assistant, School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China. He received his B.Eng, M.Eng and Ph.D degree from University of Electronic Science and Technology of China in 2011, 2014 and 2019, and has been a visiting scholar of Kyoto University from 2018 to 2019. His main research interests include manifold learning, metric learning, deep learning, subspace clustering and sparse representation in computer vision and machine learning, with focuses on human action detection and recognition, face detection and recognition, person detection and re-identification, remote sensing image processing, and medical image analysis. Cong Shi is a Research Professor in the School of Microelectronics and Communication Engineering, at Chongqing University, China. He received his PhD from Tsinghua University and has held the position of Postdoctoral Fellow with the Schepens Eye Research Institute, at Harvard Medical School. His research focuses on AI-based visual processing system-on-chips, and algorithm hardware co-design techniques. He has published over 30 papers. Ji Liu is the Head of the AI platform department and the director of the Seattle AI lab for Kwai Inc. He has previously been a faculty member in computer science at the University of Rochester, USA. He received his PhD from the University of Wisconsin-Madison. His research includes machine learning, optimization, computer vision, reinforcement learning, and other areas. He has published over 100 papers.