Ruixue Yu

Guilin University of Electronic Technology

Papers

Total Citations

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About

Ruixue Yu is a researcher at the forefront of precision agriculture and computer vision, with a focus on developing intelligent systems for automated crop harvesting. Her most-cited work, "SN-YOLO: A Rotation Detection Method for Tomato Harvest in Greenhouses," introduces a novel deep learning approach that addresses the critical challenge of accurately detecting tomato fruits under variable lighting and cluttered greenhouse conditions. By enhancing the YOLO framework with rotation-sensitive detection, Yu’s method significantly improves the reliability of vision-guided robotic harvesters, a key component in advancing agricultural automation. This paper has already garnered early citations, reflecting its timely impact on the field. Yu’s contributions lie at the intersection of robotics, machine learning, and sustainable farming, offering practical solutions to reduce labor dependency and increase crop yield efficiency. Her work exemplifies how cutting-edge AI can be tailored to real-world agricultural constraints, making her a promising voice in the growing domain of smart farming technologies.