Pengfei Zhao
Papers
1
Total Citations
2
H-Index
1
About
Pengfei Zhao is a researcher specializing in computer vision and industrial defect detection, with a particular focus on applying deep learning to pipeline weld inspection. His most-cited work, "YOLOv8_CB: An Improved YOLOv8 Model with CBAM and BiFPN for Pipeline Girth Weld Defect Detection" (2024), introduces a novel enhancement to the YOLOv8 object detection framework by integrating Convolutional Block Attention Module (CBAM) and Bidirectional Feature Pyramid Network (BiFPN). This innovation significantly improves the accuracy and efficiency of detecting subtle weld defects in critical pipeline infrastructure, addressing a key challenge in industrial safety and quality control. While his citation count is still growing—reflecting the recent publication of his work—Zhao’s contribution is notable for its practical engineering impact, offering a robust solution that balances detection speed and precision. His research bridges the gap between state-of-the-art AI architectures and real-world industrial applications, making him a promising voice in the field of applied computer vision. As his work gains traction, it is poised to influence both academic research and industrial inspection practices.
Research Focus
Key Achievements
Top Papers
- 1