LiDAR sensors are almost indispensable for autonomous robots to perceive the surrounding
environment. However, the transmission of large-scale LiDAR point clouds is highly …

The uneven and complicated porose microstructure of thermal barrier coatings brings a big
challenge for accurate and reliable thickness measurement due to the resultant change of …

Image superresolution (SR) is a task to enhance low-resolution (LR) images to high
resolution (HR) and is broadly used in applications, such as surveillance, medical diagnosis …

Deep learning-based image super-resolution (SR) methods have attracted growing interest
due to their outstanding performance. However, most of these methods assume that the …

It is quite simple for foreign objects to attach themselves to transmission line corridors
because of the wide variety of laying and the complex, changing environment. If these …

Automobiles are the primary means of transportation and increased traffic leads to the
emphasis on techniques for safe transportation. Vehicle brake light detection is essential to …

Image super-resolution reconstruction is one of the methods to improve resolution by
learning the inherent features and attributes of images. However, the existing super …

The increasing penetration of distributed energy resources (DERs) will decrease the
rotational inertia of the power system and further degrade the system frequency stability. To …

Deep learning (DL) is widely used in ship detection, but there are still some problems in the
effective classification, such as inaccurate object feature extraction and inconspicuous …

In this paper, we collect an ocular B-ultrasound image dataset and propose a Collaborative
Monitoring Deep Learning (CMDL) method to detect cataract. In the ocular B-ultrasound …