Papers
6
Total Citations
141
H-Index
6
About
Zhouzhou Zheng is a leading researcher in agricultural robotics and computer vision, specializing in intelligent harvesting systems for jujube fruits. His work focuses on developing deep learning models for object detection, autonomous navigation, and visual perception in complex orchard environments. Zheng’s major contributions include the creation of AGHRNet, an attention-based ghost-HRNet that precisely confirms catch-and-shake locations for vibration harvesting, and MLG-YOLO, a real-time detection model for winter jujubes in cluttered settings. He also pioneered an autonomous navigation method for harvesting robots using convolutional neural networks, and an improved PSPNet for trunk diameter measurement, critical for effective vibration harvesting. With over 140 citations across his most-cited papers, Zheng’s research has significantly advanced the accuracy and efficiency of robotic fruit harvesting, particularly for small, hard-to-detect jujubes. His work on winter jujube detection, which addresses challenges of small fruit size and complex backgrounds, provides essential technical support for developing practical harvesting robots, making him a key figure in precision agriculture and agricultural automation.
Research Focus
Key Achievements
Top Papers
- 1
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- 3Research on Winter Jujube Object Detection Based on Optimized Yolov5s23 citations · 2023
- 4
- 5A Diameter Measurement Method of Red Jujubes Trunk Based on Improved PSPNet19 citations · 2022
- 6