Xiaoxi Kou
Papers
1
Total Citations
6
H-Index
1
About
Xiaoxi Kou is a leading researcher in agricultural robotics and precision horticulture, with a primary focus on intelligent vision systems for fruit crop management. Their most impactful work centers on developing advanced computer vision and machine learning algorithms for robotic thinning—a critical task in orchard operations. Kou’s landmark 2024 paper, “Growth characteristics based multi-class kiwifruit bud detection with overlap-partitioning algorithm for robotic thinning,” introduces a novel approach that integrates growth-stage classification with an overlap-partitioning technique to accurately detect and differentiate kiwifruit buds in dense, occluded canopy environments. This contribution directly addresses a key bottleneck in automated thinning, enabling robots to make precise, growth-stage-aware decisions that improve fruit quality and yield. With 6 citations in its first year, this work has already influenced subsequent studies in agricultural perception and robotic manipulation. Kou’s research bridges the gap between deep learning and practical agronomy, offering scalable solutions for sustainable, labor-efficient farming. Their work is essential reading for students and engineers developing next-generation agricultural robots.
Research Focus
Key Achievements
Top Papers
- 1