Papers
14
Total Citations
619
H-Index
10
About
Jieli Duan is a pioneering researcher in agricultural robotics and precision agriculture, with a specialized focus on fruit detection, robotic harvesting, and autonomous systems for orchard environments. His work has made transformative contributions to the application of computer vision and deep learning in automating banana cultivation tasks — a notoriously complex challenge given the unpredictable conditions of natural orchards, including variable lighting, wind disturbance, and dense foliage. Duan's most celebrated contributions include developing vision-based systems for banana rachis detection and three-dimensional localization of cut-off points (100 citations), deep learning-integrated methods for counting and detecting banana bunches (90 citations), and the lightweight YOLO-Banana neural network enabling real-time orchard detection (72 citations). His 2019 foundational work on color- and texture-based banana detection (82 citations) established early benchmarks in the field. Beyond bananas, his research extends to collision-free motion planning for litchi-picking robots, adaptive fruit-picking grippers, and stereo visual-inertial localization for orchard navigation — demonstrating impressive breadth across robotic perception, motion planning, and hardware design. With over 590 cumulative citations, Duan's work is shaping the future of intelligent, automated agricultural systems worldwide.
Research Focus
Key Achievements
Top Papers
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- 6Collision-free motion planning for the litchi-picking robot70 citations · 2021
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- 10Development of an automatic control system for a hydraulic pruning robot12 citations · 2023