Optical microcombs represent a new paradigm for generating laser frequency combs based
on compact chip-scale devices, which have underpinned many modern technological …

Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI)
applications including computer vision, speech recognition, and robotics. While DNNs …

Convolutional neural networks (CNNs) excel in a wide variety of computer vision
applications, but their high performance also comes at a high computational cost. Despite …

This book provides a structured treatment of the key principles and techniques for enabling
efficient processing of deep neural networks (DNNs). DNNs are currently widely used for …

Machine learning plays a critical role in extracting meaningful information out of the
zetabytes of sensor data collected every day. For some applications, the goal is to analyze …

Abstract Machine vision faces bottlenecks in computing power consumption and large
amounts of data. Although opto-electronic hybrid neural networks can provide assistance …

The automatic identification and diagnosis of tomato leaves diseases are highly desired in
field of agriculture information. Recently Deep Convolutional Neural networks (CNN) has …

Training an artificial neural network with backpropagation algorithms to perform advanced
machine learning tasks requires an extensive computational process. This paper proposes …

Recent years have witnessed an exponential increase in the use of mobile and embedded
devices. With the great success of deep learning in many fields, there is an emerging trend …

We show optical waves passing through a nanophotonic medium can perform artificial
neural computing. Complex information is encoded in the wavefront of an input light. The …