Jiawei Xiang
Papers
1
Total Citations
6
H-Index
1
About
Jiawei Xiang is a leading researcher in agricultural robotics and computer vision, with a primary focus on developing lightweight, high-precision detection models for automated fruit harvesting. His most notable contribution is the EDT-YOLOv8n framework, a pioneering approach that addresses critical challenges in kiwifruit detection within complex orchard environments. This work tackles the dual problems of limited computational resources on harvesting robots and occlusion among fruits, achieving robust detection accuracy while maintaining a lightweight architecture suitable for real-time deployment. The paper, published in 2025, has already garnered 6 citations, reflecting its immediate impact on the field. Xiang’s research bridges the gap between theoretical computer vision and practical agricultural automation, offering scalable solutions that enhance the efficiency and reliability of robotic harvesting systems. His work is particularly significant for students and researchers interested in edge computing, object detection, and precision agriculture, as it demonstrates how advanced YOLO-based models can be optimized for resource-constrained environments. By enabling accurate fruit detection under challenging conditions, Xiang’s contributions are paving the way for more autonomous and economically viable harvesting technologies.
Research Focus
Key Achievements
Top Papers
- 1