Papers
2
Total Citations
295
H-Index
2
About
Dr. Hua Wan is a leading researcher in agricultural computer vision and precision farming, with a focus on automated fruit detection and maturity assessment. Her pioneering work leverages deep learning and RGB-D imaging to solve real-world challenges in horticulture. Dr. Wan’s most influential contributions include the development of a multiple-scale Faster R-CNN architecture for passion fruit detection and counting, which achieved remarkable accuracy in complex orchard environments. Her 2020 paper on this method has garnered 154 citations, while her foundational 2018 study on passion fruit detection and maturity classification using Red-Green-Blue Depth images has been cited 141 times. These works collectively establish her as a key innovator in integrating computer vision with agricultural robotics, enabling non-destructive, high-throughput yield estimation and quality grading. Dr. Wan’s research directly addresses the growing need for automation in fruit production, offering scalable solutions that reduce labor costs and improve harvest efficiency. Her contributions are widely recognized for bridging the gap between deep learning theory and practical agricultural applications, making her a vital resource for students and researchers in precision agriculture and intelligent sensing.
Research Focus
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Top Papers
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