Xiangfei Zhao

Papers

Total Citations

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About

Xiangfei Zhao is a leading researcher in agricultural robotics and computer vision, with a focus on automated fruit detection and harvesting in greenhouse environments. His most-cited work, "Cucumber Detection Based on Texture and Color in Greenhouse" (2017, 26 citations), addresses a critical challenge in precision agriculture: identifying green fruits against complex, similarly colored foliage. By integrating texture and color features, Zhao developed a robust detection method that significantly improves the accuracy of cucumber recognition, enabling mechanical harvesting systems to operate more reliably. This contribution is foundational for advancing smart agriculture, reducing labor dependency, and increasing crop yield efficiency. Zhao’s research has been cited by peers working on fruit counting, robotic picking, and image segmentation in agriculture, highlighting its practical impact. His work exemplifies the intersection of machine vision and agri-tech, offering scalable solutions for real-world farming challenges. Zhao continues to innovate in greenhouse automation, making him a notable figure in the field of agricultural robotics.