Yang Xiao-ju
Papers
2
Total Citations
11
H-Index
2
About
Yang Xiao-ju is a researcher whose work sits at the intersection of agricultural robotics and machine vision, with a focused, impactful contribution to the development of intelligent harvesting systems. Her primary research areas include precision agriculture, robotic manipulation, and computer vision for fruit detection and localization. Her major contributions center on the automated harvesting of pomelo fruit, a challenging task due to the fruit’s size and the complex, occluded orchard environment. She pioneered methods for accurately recognizing pomelo fruit on trees using both traditional algorithms (chromatic aberration, K-means) and deep learning (YOLOv3), and crucially, developed a technique to determine the optimal cutting region for a picking robot by analyzing the pomelo’s centroid and pedicle growth characteristics. Her most-cited works, including “Recognition of cutting region for pomelo picking robot based on machine vision” (6 citations) and “Research On Recognition Methods of Pomelo Fruit Hanging On Trees Base On Machine Vision” (5 citations), are foundational references in this niche. Though her citation counts are modest, they reflect a highly specialized, early-stage body of work that directly addresses a real-world bottleneck in agricultural automation, establishing her as a key figure in the development of practical, vision-guided harvesting robots.
Research Focus
Key Achievements
Top Papers
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