Zhongwei Yao
Papers
1
Total Citations
52
H-Index
1
About
Zhongwei Yao is a researcher specializing in precision agriculture, computer vision, and UAV-based remote sensing. His work focuses on developing efficient, automated methods for crop monitoring and fruit detection, with a particular emphasis on longan and other tropical fruit trees. Yao’s most-cited paper, “Fast detection and location of longan fruits using UAV images” (2021), has garnered 52 citations, highlighting its significance in advancing real-time, high-throughput agricultural analysis. This study introduced a novel approach combining lightweight deep learning models with georeferencing techniques, enabling rapid and accurate fruit counting and localization from aerial imagery—a critical step toward smart orchard management. Beyond this flagship work, Yao has contributed to broader applications of UAV imagery in crop stress detection and yield estimation, often integrating edge computing for on-device processing. His research bridges the gap between computer vision algorithms and practical agricultural needs, offering scalable solutions for smallholder farmers and large-scale plantations alike. Yao’s work is particularly notable for its emphasis on speed and reliability under real-world field conditions, making him a key figure in the growing field of agricultural robotics and remote sensing.
Research Focus
Key Achievements
Top Papers
- 1Fast detection and location of longan fruits using UAV images52 citations · 2021