Sun‐Ok Chung
Papers
2
Total Citations
6
H-Index
1
About
Sun-Ok Chung is a leading researcher in precision agriculture and smart farming, with a focus on developing autonomous systems and deep learning applications for agricultural machinery. His major contributions include pioneering work on tillage boundary detection for autonomous tractors, where he developed a novel RGB imagery classification method that integrates image cropping, object classification, area segmentation, and boundary detection to enable fully autonomous field operations. This work, published in 2020, has garnered 5 citations and represents a significant step toward reducing manual labor in farming. Chung also played a key role in compiling the use cases of emerging technologies in precision agriculture, as demonstrated by his contribution to the 10th Asian-Australasian Conference on Precision Agriculture (ACPA10) in 2024, which highlights the transformative potential of technology in the field. His research bridges computer vision and agricultural engineering, offering practical solutions for real-world farming challenges. With a career dedicated to advancing smart farming, Chung’s work continues to influence the development of autonomous agricultural systems, making him a notable figure in the precision agriculture community.
Research Focus
Key Achievements
Top Papers
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- 2