Yuanfan Yu
Papers
1
Total Citations
17
H-Index
1
About
Yuanfan Yu is a leading researcher in industrial robotics and intelligent manufacturing, with a primary focus on surface defect detection and quality control systems. His most cited work, "Surface Defect Detection of Hot Rolled Steel Based on Attention Mechanism and Dilated Convolution for Industrial Robots" (2023, 17 citations), addresses a critical challenge in automated manufacturing: accurately identifying defects in raw materials during production. Yu's key contribution lies in integrating attention mechanisms with dilated convolutional neural networks, enabling industrial robots to simultaneously perform two distinct defect detection tasks with enhanced precision. This innovation significantly improves the reliability of quality inspection in hot steel rolling processes, where traditional methods often struggle with varying defect types and scales. His research bridges computer vision and robotic automation, offering practical solutions for real-world manufacturing environments. By tackling the inherent complexity of multi-task defect detection, Yu's work has direct implications for reducing waste, improving production efficiency, and advancing smart factory capabilities. His findings are particularly valuable for engineers developing autonomous inspection systems in metalworking and heavy industries.
Research Focus
Key Achievements
Top Papers
- 1