Papers
1
Total Citations
2
H-Index
1
About
Minjie Xu is a researcher at the forefront of agricultural robotics and intelligent perception, with a primary focus on developing automated solutions for precision horticulture. Their most-cited work, "Research on Positioning Technology of Facility Cultivation Grape Based on Transfer Learning of SSD MobileNet" (2022, 2 citations), tackles the critical challenge of labor shortages in grape harvesting by advancing 3D spatial recognition for picking robots. By integrating transfer learning with the SSD MobileNet architecture, Xu enables efficient and accurate localization of fruit in complex greenhouse environments—a foundational step toward fully autonomous harvesting systems. This contribution bridges computer vision and agricultural engineering, demonstrating how lightweight deep learning models can be deployed for real-time, field-ready applications. While their citation count reflects an early-career trajectory, the practical implications of their work are significant, addressing a pressing need in modern agriculture. Xu’s research not only enhances robotic picking accuracy but also reduces dependency on manual labor, making it a valuable resource for students and engineers exploring smart farming technologies. Their work exemplifies the growing intersection of AI and sustainable food production.
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Top Papers
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