Ji‐Hun Yoon
Papers
2
Total Citations
12
H-Index
2
About
Ji-Hun Yoon is a researcher at the forefront of surgical data science, with a primary focus on computer vision and machine learning for minimally invasive procedures. His work centers on instrument localization and detection in laparoscopic and robotic surgeries, addressing critical challenges in surgical workflow analysis and automation. Yoon’s most notable contribution is the development of the hSDB-instrument database, a specialized instrument localization resource for laparoscopic and robotic surgeries, which has garnered 7 citations and serves as a foundational dataset for the field. He has also advanced semi-supervised learning techniques to tackle class imbalance in surgical instrument detection, achieving 5 citations for this work. These contributions are vital for enhancing real-time surgical assistance and safety. Yoon’s research bridges the gap between clinical practice and artificial intelligence, offering practical solutions for instrument tracking in complex surgical environments. His work is particularly impactful for students and researchers interested in applying deep learning to medical imaging, as it provides both benchmark datasets and novel training methodologies.
Research Focus
Key Achievements
Top Papers
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