Qingkai Zhou

ORCID: 0000-0003-2215-1697
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About
Contact & Profiles
Research Areas
  • Visual Attention and Saliency Detection
  • Remote Sensing and LiDAR Applications
  • Advanced Neural Network Applications
  • Advanced Image Fusion Techniques
  • Image and Video Quality Assessment
  • Power Line Inspection Robots
  • Occupational Health and Safety Research
  • Robotics and Sensor-Based Localization
  • Infrared Target Detection Methodologies
  • Quality and Safety in Healthcare
  • Digital Transformation in Industry

Tsinghua University
2023

Hohai University
2022

The existing unmanned aerial vehicle (UAV)-based electric transmission line inspection systems generally adopt manual control and follow the predefined path, which reduces efficiency makes a high cost. In this article, UAV system with advanced embedded processors binocular visual sensors is developed to generate guidance information from power lines in real-time achieve automatic inspection. To realize 3-D autonomous perception of lines, we first propose an end-to-end convolutional neural...

10.1109/tim.2022.3169555 article EN IEEE Transactions on Instrumentation and Measurement 2022-01-01

The intelligent health management for vehicle steering system often faces problems like history data dependency and limited faulty samples. Digital twins (DT) have the potential to solve these problems. However, advantages of DT might be lost due prior physics knowledge, heterogeneity, healthy physical In this paper, Weighted Feature Space Measure Barycenter Averaging-Wasserstein Generative Twin architecture (WFSMBA-WGDT) is proposed. WFSMBA algorithm designed through a low-dimension feature...

10.1109/phm-hangzhou58797.2023.10482702 article EN 2023-10-12
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