Jiawei Shi
Papers
2
Total Citations
71
H-Index
2
About
Jiawei Shi is a rising force in precision agriculture and intelligent field robotics, with research centered on computer vision, deep learning, and automated crop management. His major contributions lie in developing lightweight, high-efficiency algorithms tailored for real-time agricultural tasks. In his highly cited work "Seedling-YOLO," Shi introduced a novel target detection algorithm based on YOLOv7-Tiny that dramatically improves the accuracy of assessing broccoli seedling transplanting quality, addressing critical issues of false and missed detections in robotic field management—a paper that has already garnered 40 citations. Complementing this, his "SN-CNN" paper (31 citations) presents a streamlined convolutional neural network for extracting crop row centerlines in ridge-planted vegetables, enabling precise autonomous navigation for seedling-stage field operations. Together, these innovations demonstrate Shi’s ability to bridge the gap between complex deep learning models and practical, deployable solutions for agriculture. His work is pivotal for advancing smart farming, reducing labor dependency, and enhancing crop yield through real-time, on-the-ground robotic intelligence.
Research Focus
Key Achievements
Top Papers
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