Papers
2
Total Citations
87
H-Index
2
About
Meonghun Lee is a leading researcher at the intersection of artificial intelligence and precision agriculture, with a primary focus on developing autonomous systems for smart farming. His most impactful work, an artificial intelligence approach for tomato detection and mass estimation in precision agriculture, has garnered 82 citations and demonstrates his expertise in computer vision and robotics for agricultural applications. This research addresses critical challenges in yield monitoring by enabling accurate, non-destructive estimation of crop mass through image processing techniques. Lee has also made significant contributions to autonomous agricultural machinery, developing deep learning-based methods for tillage boundary detection that allow tractors to navigate and operate without human intervention. His work on RGB imagery classification for autonomous tractors represents an important step toward fully automated farming operations. Through his research, Lee is helping to advance the practical implementation of AI and robotics in agriculture, addressing key challenges in crop monitoring, yield estimation, and autonomous field operations that are essential for improving agricultural efficiency and sustainability.
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Top Papers
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