We present a class of efficient models called MobileNets for mobile and embedded vision
applications. MobileNets are based on a streamlined architecture that uses depth-wise …

The ionic defects at the surfaces and grain boundaries of organic–inorganic halide perovskite
films are detrimental to both the efficiency and stability of perovskite solar cells. Here, we …

All highly-efficient organic–inorganic halide perovskite (OIHP) solar cells to date are made of
polycrystalline perovskite films which contain a high density of defects, including point and …

This technical note is concerned with the distributed Kalman filtering problem for a class of
networked multi-sensor fusion systems (NMFSs) with missing sensor measurements, random …

We present the next generation of MobileNets based on a combination of complementary
search techniques as well as a novel architecture design. MobileNetV3 is tuned to mobile …

Designing convolutional neural networks (CNN) for mobile devices is challenging because
mobile models need to be small and fast, yet still accurate. Although significant efforts have …

As one unique group of two-dimensional (2D) nanomaterials, 2D metal nanomaterials have
drawn increasing attention owing to their intriguing physiochemical properties and broad …

The rising popularity of intelligent mobile devices and the daunting computational cost of
deep learning-based visual recognition models call for efficient on-device inference schemes. …

Metalenses consist of an array of optical nanoantennas on a surface capable of manipulating
the properties of an incoming light wavefront. Various flat optical components, such as …

Learning fine-grained image similarity is a challenging task. It needs to capture between-class
and within-class image differences. This paper proposes a deep ranking model that …