Myeong Yong Kang
Papers
3
Total Citations
46
H-Index
3
About
Myeong Yong Kang is pioneering the integration of artificial intelligence and digital twin technology to revolutionize modern agriculture, with a sharp focus on smart farming and precision harvesting. His work addresses critical challenges in food security by developing advanced computer vision systems for fruit detection and robotic harvesting. Kang’s 2024 paper on digital twins in livestock farming, already garnering 24 citations, outlines a visionary framework for using virtual replicas to mitigate climate change impacts on agricultural production. He is perhaps best known for his lightweight YOLOv5s-CGhostnet model (15 citations), which dramatically improves strawberry maturity detection and counting for harvesting robots, balancing high accuracy with computational efficiency. More recently, his DF-Mask R-CNN approach (7 citations) tackles the delicate problem of peduncle detection and monocular depth estimation, enabling robots to pick ripe strawberries without bruising. By making deep learning models both robust and deployable on resource-constrained hardware, Kang is bridging the gap between cutting-edge AI research and practical, scalable solutions for sustainable agriculture.
Research Focus
Key Achievements
Top Papers
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