Haowei Zhu
Papers
1
Total Citations
2
H-Index
1
About
Haowei Zhu is a leading researcher in agricultural robotics and precision fruit harvesting, with a focus on integrating advanced computer vision and deep learning to improve post-harvest fruit quality. His most cited work, "Accurate Apple Fruit Stalk Cutting Technology Based on Improved YOLOv8 with Dual Cameras" (2025), addresses a critical bottleneck in automated picking: preserving the fruit stalk to maintain freshness and reduce spoilage. Zhu’s major contribution lies in designing a two-camera, two-stage detection and shearing system that enhances the accuracy of apple and stalk localization using an improved YOLOv8 network. By modeling the mechanical shearing process, his research directly improves the reliability of robotic harvesters, reducing damage to both fruit and tree. Though early in its citation impact, this work has already garnered attention for its practical, field-ready approach. Zhu’s achievements include bridging the gap between deep learning object detection and real-world agricultural engineering, offering a scalable solution for the fresh fruit industry. His work is essential reading for researchers in precision agriculture, computer vision, and robotics, demonstrating how targeted AI improvements can solve longstanding challenges in automated crop handling.
Research Focus
Key Achievements
Top Papers
- 1