Papers
7
Total Citations
396
H-Index
5
About
Longzhe Quan is a leading researcher in agricultural robotics and precision farming, with a focus on intelligent weed control and crop monitoring. His work centers on developing autonomous systems that integrate deep learning and computer vision to address critical challenges in field operations. A major contribution is the creation of an intelligent intra-row robotic weeding system that combines deep learning with a targeted weeding mode, significantly reducing herbicide use while improving efficiency. This work, published in 2022, has already garnered over 107 citations. His 2019 paper on maize seedling detection using an improved Faster R–CNN, cited 189 times, is a foundational study for crop recognition under complex field conditions. Quan has also advanced crop row-following algorithms and patch-spraying accuracy, with his 2023 paper on combined error adjustment for agricultural robots receiving 20 citations. Beyond weeding, he has designed a spherical robot for stem diameter inspection, an important parameter for monitoring plant growth and moisture content. With over 390 total citations, Quan’s research is driving the next generation of smart, sustainable agriculture.
Research Focus
Key Achievements
Top Papers
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- 6Design and test of stem diameter inspection spherical robot5 citations · 2019
- 7Design and test of stem diameter inspection spherical robot2 citations · 2019