Fanglei Dai
Papers
1
Total Citations
17
H-Index
1
About
Fanglei Dai is a researcher at the forefront of intelligent manufacturing and computer vision, with a primary focus on automated welding and robotic perception. His most notable contribution is the development of a unified framework based on semantic segmentation for extracting weld seam profiles across typical joint types, published in 2024. This work, which has already garnered 17 citations, addresses a critical challenge in industrial automation: enabling robots to accurately identify and track complex weld geometries in real time. By integrating deep learning with traditional image processing, Dai’s framework significantly enhances the precision and adaptability of welding systems, reducing human error and improving production efficiency. His research bridges the gap between theoretical computer vision and practical manufacturing applications, offering scalable solutions for industries like automotive and shipbuilding. With a growing citation record, Dai is establishing himself as a key innovator in the field of intelligent welding and robotic vision, paving the way for more autonomous and reliable industrial processes.
Research Focus
Key Achievements
Top Papers
- 1