Yueyue Zhang

Papers

Total Citations

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About

Yueyue Zhang is a leading researcher in agricultural robotics and computer vision, with a focused expertise in automated fruit detection and harvesting systems. Her work primarily addresses the critical challenge of automating the picking of dragon fruit, a labor-intensive crop prevalent in China and Southeast Asia. Zhang’s major contributions include pioneering deep learning detection methods tailored to the unique morphological challenges of dragon fruit, such as their hard branches and complex postures. Her highly cited paper, "A Dragon Fruit Picking Detection Method Based on YOLOv7 and PSP-Ellipse" (2023, 51 citations), introduced a novel approach combining YOLOv7 with a PSP-Ellipse module to enhance detection accuracy for automated picking. Building on this, her work "RDE-YOLOv7: An Improved Model Based on YOLOv7 for Better Performance in Detecting Dragon Fruits" (2023, 41 citations) further refined visual guidance systems for picking robots, significantly improving detection robustness. With over 90 combined citations in just two years, Zhang’s research is instrumental in advancing precision agriculture, reducing labor intensity, and enabling scalable automation for specialty crops. Her achievements underscore a commitment to bridging AI and agri-tech, offering practical solutions for sustainable farming.