Jiahua Wu
Papers
6
Total Citations
292
H-Index
5
About
Jiahua Wu is a leading researcher in agricultural robotics, specializing in computer vision and autonomous navigation for greenhouse harvesting systems. His work focuses on developing robust algorithms that enable robots to perceive and navigate complex agricultural environments, particularly for cucumber and tomato picking. Wu’s major contributions include the prediction-point Hough transform and median point Hough transform for extracting navigation paths in greenhouses, which have collectively garnered over 170 citations. He has also advanced fruit detection under challenging conditions, proposing an improved YOLOv3 architecture with dual path networks for cherry tomatoes, cited 51 times, and methods for detecting ripe fruits under natural occlusion and variable illumination, cited 48 times. His innovative use of convolutional auto-encoders for image restoration further enhances robot perception in degraded environments. With over 290 total citations across his most-cited works, Wu’s research directly addresses the practical challenges of deploying robots in unstructured agricultural settings, making his work essential for students and researchers in precision agriculture and field robotics.
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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