This paper proposes an innovative object detector by leveraging deep features learned in
high-level layers. Compared with features produced in earlier layers, the deep features are …

Due to the difficulty in acquiring massive task-specific occluded images, the classification of
occluded images with deep convolutional neural networks (CNNs) remains highly …

Objective To systematically evaluate the prevalence of Diabetes Distress (DD) in type 2
diabetes mellitus (T2DM) patients in China. Methods The PubMed, PsycInfo, Web of Science, …

Deep learning has achieved exciting results in face recognition; however, the accuracy is
still unsatisfying for occluded faces. To improve the robustness for occluded faces, this paper …

Classification of partially occluded images is a highly challenging computer vision problem
even for the cutting-edge deep learning technologies. To achieve a robust image …

This paper considers observer-based actuator fault detection and reconstruction problems
for uncertain nonlinear systems. Based on a kind of full-order observer which is robust to …

Purpose: To investigate the possible mechanism of miR-210 involved in epithelial–mesenchymal
transition (EMT) of pancreatic cancer cells under hypoxia. Methods: In this study, we …

On the adhesion characteristics of pavement surfaces, the impacts of new interface bonding
material (GY), modified emulsified asphalt (RH), and secondary epoxy bonding oil (HRB) …

Purpose: The process of making the most of digital tools in the workplace to support an
organization's success is known as" leveraging on technology." By automating manual tasks …

In order to study the synergistic effect of polymer and conductive functional materials on the
properties of cement-based materials, polymer conductive cement-based materials were …