Jiangang Yi
Papers
2
Total Citations
4
H-Index
1
About
Jiangang Yi is a researcher at the forefront of intelligent automation and industrial safety, with a primary focus on computer vision and robotic manipulation for hazardous environments. His work uniquely bridges deep learning and practical engineering, addressing critical challenges in both mining and renewable energy sectors. Yi’s most notable contribution is the development of an intelligent emulsion explosive grasping and filling system for tunnel blasting robots. This system, detailed in his 2024 paper (3 citations), integrates a custom YOLO-SimAM-GRCNN architecture that combines real-time blast hole detection with precise robotic control, significantly enhancing safety and efficiency in explosive handling. More recently, Yi has extended his expertise to solar energy infrastructure, proposing an enhanced YOLOv9 algorithm for detecting stains and damage in photovoltaic panels (2025, 1 citation). This work demonstrates his versatility in applying advanced object detection to critical maintenance tasks. Through these innovations, Yi is advancing the frontier of autonomous systems in high-risk industrial settings, with his research already influencing practical applications in tunneling and solar farm operations.
Research Focus
Key Achievements
Top Papers
- 1
- 2