Liangen Yang

Hubei University of Technology

Papers

1

Total Citations

2

H-Index

1

About

Dr. Liangen Yang is a researcher whose work bridges the fields of mechanical engineering and computational image analysis, with a particular focus on applying fractal geometry to industrial automation. His key research areas include image classification, pattern recognition, and the characterization of complex mechanical components. Dr. Yang’s major contribution lies in demonstrating that the fractal dimension—a measure of shape complexity and self-similarity—can serve as a powerful, quantitative feature for classifying and recognizing irregular mechanical parts. This approach offers a novel, mathematically rigorous method for automated quality control and part identification in manufacturing settings. While his most-cited paper, "Image classification and recognition method to mechanical parts based on fractal dimension" (2017), has garnered 2 citations, its conceptual foundation is significant for its potential to guide future work in intelligent manufacturing and non-destructive evaluation. Dr. Yang’s research provides a compelling example of how abstract mathematical concepts can be translated into practical engineering solutions, opening new pathways for the automation of visual inspection tasks.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Image classification and recognition method to mechanical parts based on fractal dimension
2 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Hubei University of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago