Jinhong Ding

Shanghai Jiao Tong University

Papers

1

Total Citations

4

H-Index

1

About

Jinhong Ding’s research lies at the intersection of computer vision, intelligent robotics, and industrial automation, with a particular focus on autonomous systems for manufacturing. His most notable contribution is the development of a grid-based line segment detector, a novel vision algorithm designed to enhance robotic perception in complex environments. This work, published in 2021, directly addresses a critical challenge in the shipbuilding industry: enabling robots to perform tasks like welding without extensive pre-programming or human intervention. By integrating this detector into a vision system for autonomous ship small assembly lines, Ding demonstrated how robots can interpret their surroundings in real time, paving the way for more flexible and efficient production. While his most-cited paper has garnered 4 citations—a modest number reflecting the niche, applied nature of the work—its impact is significant within the field of industrial robotics. Ding’s research bridges the gap between theoretical computer vision and practical engineering, offering a scalable solution for intelligent manufacturing. His achievements highlight a commitment to advancing automation in heavy industries, making him a valuable contributor to the future of smart factories and autonomous robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Gird Based Line Segment Detector and Application: Vision System for Autonomous Ship Small Assembly Line
4 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Shanghai Jiao Tong University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago