Haixia Sun
Papers
6
Total Citations
76
H-Index
5
About
Haixia Sun is a prominent researcher specializing in agricultural computer vision, intelligent detection systems, and precision horticulture automation. Her work focuses on developing lightweight deep learning models — particularly adaptations of the YOLO (You Only Look Once) architecture — to solve real-world challenges in automated fruit detection and robotic harvesting across complex, unstructured agricultural environments. Sun's most significant contributions include pioneering detection frameworks tailored to specific crops, including "Yuluxiang" pears, flat jujube, "Okubo" peaches, and cucumbers. Her models address persistent challenges such as fruit-background color similarity, occlusion by foliage, fruit bagging, and variable lighting conditions — barriers that have long hindered agricultural robotics. Her 2024 FPG-YOLO paper, targeting stamen detection for assisted pollination, reflects a particularly innovative expansion of machine vision into delicate orchard operations. Collectively accumulating over 75 citations since 2022, her body of work has gained rapid recognition within the precision agriculture community. By consistently balancing model accuracy with computational efficiency, Sun's research directly advances the feasibility of real-time, on-device deployment in fruit-thinning and harvesting robots — contributing meaningfully to reducing agricultural labor costs and improving crop quality at scale.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6