Changying Ji
Papers
6
Total Citations
42
H-Index
3
About
Changying Ji is a pioneering figure in agricultural robotics, whose research centers on machine vision, autonomous navigation, and intelligent harvesting systems. His most impactful contribution is the development of a machine vision-based cotton recognition method for harvesting robots, which uses color subtraction to accurately identify cotton from its surroundings—enabling precise manipulator control for automated picking. This foundational work, published in 2008, has garnered 27 citations and remains a key reference in the field. Ji has also advanced vision-based navigation for agricultural robots, proposing algorithms that leverage illumination-invariant images to ensure reliable operation under varying field conditions. More recently, he has focused on real-time pest monitoring, co-developing the lightweight RSCDet model for aphid detection in cereal crops, deployable on embedded systems like the NVIDIA Jetson TX2 NX for low-cost, portable monitoring. His broader contributions include comprehensive reviews of mobile platform trends and designs for wheeled robots with omnidirectional steering. With a career spanning from foundational vision algorithms to cutting-edge edge-computing applications, Ji’s work directly addresses the practical challenges of precision agriculture, making him a respected authority in the integration of robotics and crop management.
Research Focus
Key Achievements
Top Papers
- 1Machine Vision Based Cotton Recognition for Cotton Harvesting Robot27 citations · 2008
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- 4Object Recognition on Cotton Harvesting Robot Using Human Visual System2 citations · 2012
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