Zicong Xie

Papers

1

Total Citations

21

H-Index

1

About

Dr. Zicong Xie is a leading researcher in industrial automation and machine vision, with a primary focus on advancing quality control systems for lithium battery manufacturing. His most influential work, "Research on detection algorithm of lithium battery surface defects based on embedded machine vision" (2021, 21 citations), addresses a critical bottleneck in battery production: the reliance on error-prone manual inspection. By developing an embedded machine vision algorithm, Dr. Xie introduced a robotic visual inspection system that significantly reduces human workload and detection errors, enhancing both efficiency and reliability in high-stakes manufacturing environments. This contribution is pivotal as the global demand for safer, higher-quality lithium batteries surges. Dr. Xie’s research bridges computer vision, embedded systems, and industrial robotics, offering practical solutions for real-time defect detection. His work has been recognized for its direct industrial applicability, earning citations from peers in manufacturing engineering and automation. For students and researchers, Dr. Xie exemplifies how targeted algorithm design can transform traditional production lines into intelligent, automated systems—a key step toward Industry 4.0.

Research Focus

Key Achievements

1
H-Index
1
Papers
21
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Research on detection algorithm of lithium battery surface defects based on embedded machine vision
21 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 6

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago