Yuehua Zhao
Papers
2
Total Citations
88
H-Index
2
About
Dr. Yuehua Zhao is a leading researcher in agricultural robotics and computer vision, with a focus on enabling intelligent automation for complex real-world environments. Her primary research areas include deep learning-based object detection, 6D pose estimation, and robotic manipulation. Dr. Zhao’s most impactful contribution is her work on apple detection in orchards, where she developed an improved YOLOv4 model that significantly enhances detection accuracy under challenging conditions like variable lighting and occlusions. This paper has garnered 80 citations, underscoring its influence on precision agriculture and autonomous harvesting systems. More recently, she has advanced category-level 6D pose estimation, introducing a geometry-guided instance-aware prior and multi-stage reconstruction method to enable robots to perceive and interact with unseen object instances—a critical step for general-purpose robotic manipulation. This work, with 8 citations, is gaining traction in the robotics and augmented reality communities. Dr. Zhao’s research bridges the gap between state-of-the-art computer vision and practical agricultural automation, earning her recognition as a key innovator in smart farming technologies.
Research Focus
Key Achievements
Top Papers
- 1Apple Detection in Complex Scene Using the Improved YOLOv4 Model80 citations · 2021
- 2