Shi Dong
Papers
1
Total Citations
18
H-Index
1
About
Shi Dong is a researcher at the forefront of agricultural robotics and computer vision, specializing in the automation of fruit harvesting. His most-cited work, "Selective fruit harvesting prediction and 6D pose estimation based on YOLOv7 multi-parameter recognition" (2024), has already garnered 18 citations, reflecting its immediate impact on precision agriculture. Dong’s major contribution lies in integrating deep learning with robotic manipulation, developing algorithms that not only detect ripe fruit but also predict optimal harvesting sequences and estimate six-degree-of-freedom poses for robotic arms. This work addresses a critical bottleneck in agricultural automation—enabling selective, non-destructive picking in complex orchard environments. By leveraging YOLOv7’s multi-parameter recognition, Dong has advanced the accuracy of fruit detection under variable lighting and occlusion conditions, a key challenge for field robotics. His research bridges the gap between computer vision and practical agricultural engineering, offering scalable solutions for labor-intensive industries. With a growing citation record and a focus on real-world deployment, Shi Dong is establishing himself as a leading voice in the intersection of AI and sustainable food production.
Research Focus
Key Achievements
Top Papers
- 1