Chapter 4: Efficient methods for deep learning☆
Han Cai; Ji Lin; Song Han Massachusetts Institute of Technology, Cambridge, MA, United States
Abstract
Deep neural networks (DNNs) have achieved unprecedented success in computer vision. However, their superior performance comes at the considerable cost of computational complexity, which greatly hinders their applications in many resource-constrained devices, such as mobile phones and Internet of Things (IoT) devices. Therefore, methods and techniques that can lift the efficiency bottleneck while preserving the high accuracy of DNNs are in great demand to enable numerous edge AI applications. This chapter provides an overview of efficient deep learning methods. We start from introducing popular ...
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