Dae Yeong Kang
Papers
3
Total Citations
46
H-Index
3
About
Dae Yeong Kang is at the forefront of smart agriculture, pioneering the integration of artificial intelligence and digital twin technology to revolutionize livestock and crop production. His research primarily focuses on precision farming, computer vision for automated harvesting, and climate-resilient agricultural systems. Kang’s most impactful work, “From Reality to Virtuality: Revolutionizing Livestock Farming Through Digital Twins” (2024, 24 citations), addresses the urgent need for adaptive farming methodologies in the face of climate change-induced food insecurity. He has made significant contributions to robotic harvesting by developing lightweight detection algorithms, such as the improved YOLOv5s-CGhostnet (2024, 15 citations), which enables efficient strawberry maturity classification and counting for harvesting robots. His innovative DF-Mask R-CNN approach (2025, 7 citations) further advances precision agriculture by accurately localizing peduncle picking points using monocular depth estimation, minimizing fruit damage during robotic harvesting. Kang’s work bridges the gap between virtual simulations and real-world agricultural challenges, offering scalable solutions for sustainable food production. With growing citation impact and cutting-edge methodologies, he is establishing himself as a key innovator in smart farming technologies.
Research Focus
Key Achievements
Top Papers
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