Chenxi An

Northeastern University

Papers

1

Total Citations

2

H-Index

1

About

Chenxi An is a researcher specializing in industrial defect detection and intelligent manufacturing, with a particular focus on advanced computer vision and deep learning techniques for quality inspection. Their most notable contribution is the development of a two-stage detection strategy for identifying internal surface defects in seamless steel pipes, a critical challenge in heavy industry. This innovative approach combines a suspected defect filtering mechanism with a parallel-encoder-based segmentation model, significantly improving detection accuracy and efficiency. Though a recent publication from 2025, this work has already garnered 2 citations, signaling growing interest in their practical, scalable solutions. Chenxi An’s research bridges the gap between theoretical machine learning and real-world industrial applications, addressing pressing needs in manufacturing automation. Their work stands out for its methodological rigor and potential to reduce waste and enhance safety in steel production. As a rising voice in the field, Chenxi An continues to push boundaries in defect detection, with future contributions likely to shape smart manufacturing and quality control systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A two-stage detection strategy for seamless steel pipe internal surface defects: From suspected defect filtering to parallel-encoder-based segmentation
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Northeastern University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago