Papers
28
Total Citations
931
H-Index
16
About
Yongjie Cui is a leading researcher in agricultural robotics, with a specialized focus on automating kiwifruit cultivation and harvesting operations. His work addresses one of horticulture's most pressing challenges: reducing the labor-intensive costs of fruit production, which can consume over 25% of annual kiwifruit production budgets, particularly in Shaanxi, China — the world's largest kiwifruit-producing region. Cui's most significant contributions span the full agricultural cycle, from robotic pollination to mechanical harvesting. He has pioneered machine vision systems for kiwifruit detection, employing deep learning architectures including Faster R-CNN, VGG16, and YOLOv4/v5, enabling real-time fruit and flower identification in complex orchard environments. His engineering work extends to designing integrated end-effectors, lightweight pollination arms, and sophisticated double-arm harvesting robots capable of collaborative, collision-free operation. With over 700 cumulative citations across his top publications, Cui's research has garnered substantial international recognition. His most-cited work on end-effector design (127 citations) and multi-class detection systems (99 citations) reflect his dual strength in both hardware innovation and computer vision. Beyond kiwifruit, he has also contributed to precision agriculture through machine-learning-based anomaly detection in hydroponic lettuce systems, demonstrating the broad applicability of his methodologies.
Research Focus
Key Achievements
Top Papers
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- 3Kiwifruit detection in field images using Faster R-CNN with VGG1697 citations · 2019
- 4
- 5Design of a lightweight robotic arm for kiwifruit pollination67 citations · 2022
- 6Canopy segmentation and wire reconstruction for kiwifruit robotic harvesting60 citations · 2020
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- 9Double-Arm Cooperation and Implementing for Harvesting Kiwifruit40 citations · 2022
- 10