Papers
2
Total Citations
6
H-Index
2
About
Zhimin Mei is a researcher at the forefront of agricultural robotics and intelligent automation, with a primary focus on integrating machine vision, deep learning, and 3D perception to revolutionize orchard harvesting and industrial sorting. Their major contributions include pioneering a hybrid framework that combines YOLO VX deep learning models with 3D object recognition and SLAM-based navigation for precise fruit localization and grasping, addressing a critical bottleneck in intelligent harvesting. Additionally, Mei designed a collaborative robot sorting system using machine vision for the YUMI platform, enhancing automation in production lines. While their most-cited works—such as the 2025 study on fruit localization (3 citations) and the 2021 paper on YUMI sorting (3 citations)—are early in their citation trajectory, they represent foundational steps toward practical, AI-driven solutions in agriculture and manufacturing. Mei’s work demonstrates a clear commitment to bridging advanced algorithms with real-world robotic applications, promising significant impact as the fields of precision agriculture and smart manufacturing continue to evolve.
Research Focus
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Top Papers
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