Jinzhu Lu
Papers
6
Total Citations
155
H-Index
5
About
Jinzhu Lu is a prominent researcher specializing in machine vision, deep learning, and intelligent agricultural robotics, with a particular focus on automating crop detection, segmentation, and harvesting processes. His work sits at the intersection of computer vision and precision agriculture, addressing real-world challenges in food production efficiency and sustainability. Lu's most impactful contribution is his YOLOv3-based computer vision system for tea bud identification and picking-point localization, which has garnered 106 citations and established him as a leading voice in agricultural automation. Building on this foundation, he has developed increasingly sophisticated approaches to tea bud recognition, including lightweight YOLOv5 architectures optimized for intelligent picking robots and cloud-platform-integrated semantic segmentation pipelines. His research extends beyond tea cultivation to encompass lettuce trace-element deficiency diagnosis, Sichuan pepper recognition in complex field environments, and comprehensive reviews of machine vision applications in citrus production. Collectively, Lu's publications reflect a consistent mission: replacing labor-intensive, error-prone manual processes with robust, AI-driven solutions tailored to diverse agricultural settings. With over 150 cumulative citations across his recent work, his research is making a measurable impact on the development of next-generation smart farming systems worldwide.
Research Focus
Key Achievements
Top Papers
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- 4Application of Machine Vision Technology in Citrus Production10 citations · 2023
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