Kyeong-Min Kang
Papers
1
Total Citations
2
H-Index
1
About
Kyeong-Min Kang is a researcher focused on agricultural robotics and automation, with a particular emphasis on deep learning for autonomous navigation in complex farming environments. His most cited work, "Deep learning-based path detection in citrus orchard" (2020), introduces a practical framework for enabling agricultural machinery to autonomously travel along crop rows—a critical component for farming efficiency. This study, which has garnered 2 citations, demonstrates Kang’s contribution to bridging computer vision and precision agriculture by applying deep learning to path detection in orchards, where irregular terrain and foliage pose significant challenges. His research addresses the growing need for automation in agriculture, aiming to reduce labor costs and improve operational precision. Kang’s work is notable for its focus on real-world applicability, offering a scalable solution for autonomous navigation in specialty crops like citrus. While his citation count is modest, his contributions are foundational for researchers and engineers developing field-ready agricultural robots, highlighting his role in advancing smart farming technologies.
Research Focus
Key Achievements
Top Papers
- 1