Longye Xiong
Papers
1
Total Citations
2
H-Index
1
About
Longye Xiong is a researcher specializing in agricultural image processing and precision agriculture, with a particular focus on the automated recognition and segmentation of fruit crops. His most-cited work, "A Method for Segmentation and Recognition of Mature Citrus and Branches-Leaves Based on Regional Features" (2018), introduces a novel approach that leverages regional feature analysis to distinguish mature citrus fruits from complex foliage and branch structures. This contribution addresses a critical bottleneck in robotic harvesting and yield estimation, offering a computationally efficient solution for real-time field applications. Though his citation count is modest, Xiong’s work lays foundational groundwork for integrating computer vision with agricultural robotics, emphasizing practical, low-cost methods that can be deployed in non-ideal lighting and occluded environments. His research is particularly valuable for the citrus industry, where accurate fruit detection under natural conditions remains challenging. By focusing on regional rather than pixel-level features, Xiong’s method reduces processing time while maintaining high recognition accuracy, making it a stepping stone for future advancements in automated fruit picking and crop monitoring systems.
Research Focus
Key Achievements
Top Papers
- 1