Jinqiu Gao
Papers
1
Total Citations
12
H-Index
1
About
Jinqiu Gao is a researcher focused on agricultural automation and machine vision, with a particular emphasis on improving the efficiency of leafy vegetable seedling transplanting. Her most cited work, "Detection Method and Experimental Research of Leafy Vegetable Seedlings Transplanting Based on a Machine Vision" (2022, 12 citations), addresses a critical bottleneck in automated farming: the need to accurately identify and remove empty cells or unqualified seedlings during transplanting. Gao proposed a novel method that leverages the image processor PV200 to detect key growth parameters of seedlings, enabling real-time, vision-guided sorting. This contribution is significant for reducing labor costs and increasing transplanting precision in modern horticulture. While her citation count is still growing, her work represents a practical step toward integrating computer vision into agricultural robotics. Gao’s research is particularly relevant for students and engineers working on smart farming technologies, as it demonstrates how accessible machine vision tools can be applied to solve real-world problems in plant production. Her ongoing efforts continue to advance the field of precision agriculture.
Research Focus
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Top Papers
- 1