Yongsong Zhan

Guilin University of Electronic Technology

Papers

Total Citations

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About

Dr. Yongsong Zhan is a leading researcher at the intersection of computer vision and precision agriculture, with a focus on developing intelligent systems for automated crop harvesting and monitoring. His most prominent work, "SN-YOLO: A Rotation Detection Method for Tomato Harvest in Greenhouses" (2025), addresses a critical bottleneck in vision-guided robotic harvesting: the accurate detection of tomato fruits under challenging real-world conditions, such as variable lighting and background clutter. By introducing a rotation-sensitive detection framework, Dr. Zhan’s method significantly improves the precision and robustness of fruit localization, directly enabling more reliable robotic picking in greenhouse environments. This contribution has already garnered early citations, reflecting its immediate relevance to the agricultural robotics community. Beyond this flagship study, Dr. Zhan’s research portfolio spans deep learning architectures, object detection, and sensor fusion for agricultural automation. His work is instrumental in bridging the gap between state-of-the-art computer vision algorithms and practical, deployable solutions for sustainable farming. Dr. Zhan’s innovative approach continues to shape the future of smart agriculture, making him a key figure in the field.