Haoming Wang
Papers
3
Total Citations
76
H-Index
3
About
Haoming Wang is a leading researcher in agricultural robotics, specializing in computer vision and deep learning for intelligent fruit harvesting systems. His work focuses on developing perception technologies that enable robots to detect, classify, and selectively harvest delicate berry fruits, addressing critical challenges in labor-intensive manual picking and fruit damage during mechanical harvesting. Wang's most influential contribution is the development of the YOLOv8+ model for strawberry detection and ripeness classification, which integrates advanced image processing to achieve high-accuracy, real-time identification—a key step toward fully autonomous harvesting. This work has garnered 48 citations since 2024, underscoring its immediate impact on the field. He has also authored a comprehensive review of perception technologies for berry fruit-picking robots, analyzing the advantages, disadvantages, and future prospects of various sensing approaches, which has accumulated 22 citations. Most recently, Wang extended his methods to litchi bunch detection and ripeness assessment using clustering techniques, demonstrating the transferability of his approach to other high-value crops. His research is pivotal in bridging the gap between laboratory algorithms and practical agricultural applications, making him a notable figure in precision agriculture and robotics.
Research Focus
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Top Papers
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