Guoqing Chen
Papers
1
Total Citations
5
H-Index
1
About
Guoqing Chen is a leading researcher in advanced manufacturing and intelligent welding technologies, with a primary focus on laser-arc hybrid welding processes. His most notable contribution is the development of a novel deep learning architecture, the local-add U-net, which enables precise tracking of weld seams even under strong interference conditions—a critical challenge in automated welding. This work, published in 2025, has already garnered 5 citations, reflecting its immediate impact on the field. Chen’s research bridges the gap between traditional welding engineering and modern computer vision, offering robust solutions for real-time quality control in industrial applications. His achievements highlight his expertise in sensor fusion, image processing, and neural network design, positioning him as a key innovator in intelligent manufacturing. For students and researchers, Chen’s work demonstrates how cutting-edge AI can solve long-standing problems in production environments, paving the way for more autonomous and reliable welding systems.
Research Focus
Key Achievements
Top Papers
- 1