Zhikui Wang
Papers
7
Total Citations
321
H-Index
6
About
Zhikui Wang is a leading researcher in agricultural robotics and computer vision, whose work is pivotal to the development of intelligent harvesting systems. His primary research areas include navigation path extraction for greenhouse robots, fruit detection under complex natural conditions, and lightweight deep learning models for real-time agricultural applications. Wang’s major contributions include the prediction-point and median point Hough transform methods for extracting navigation paths in cucumber and tomato greenhouses, which have garnered 110 and 62 citations, respectively. He also advanced fruit detection with an improved YOLOv3 model using dual path networks for cherry tomatoes (51 citations) and a method for detecting ripe fruits under natural occlusion and illumination (48 citations). His recent work, GA-YOLO, addresses dense and occluded grape detection with a lightweight model (29 citations), while his research on image restoration using convolutional auto-encoders enhances robot performance in challenging environments. With over 320 total citations, Wang’s innovations are critical for enabling efficient, automated picking in smart agriculture, directly impacting the future of sustainable farming.
Research Focus
Key Achievements
Top Papers
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- 3An improved Yolov3 based on dual path network for cherry tomatoes detection51 citations · 2021
- 4Detecting ripe fruits under natural occlusion and illumination conditions48 citations · 2021
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