Gyeongyong Heo
Papers
1
Total Citations
31
H-Index
1
About
Gyeongyong Heo is a researcher whose work sits at the critical intersection of sensor fusion, robotics, and humanitarian demining. His primary research focuses on developing advanced signal processing and hierarchical classification algorithms for landmine detection, particularly by integrating data from Wideband Electro-Magnetic Induction (WEMI) and Ground Penetrating Radar (GPR) sensors. In his most cited work (2008, 31 citations), Heo pioneered a multi-tiered algorithmic approach to discriminate both Anti-Tank (AT) and Anti-Personnel (AP) landmines from clutter, using data collected from sensors mounted on a robotic platform. This contribution is significant because it directly addresses the challenge of reducing false alarm rates in complex environments, a key bottleneck in humanitarian demining operations. By demonstrating how to fuse complementary sensor modalities in a hierarchical fashion, Heo’s research has provided a practical framework for developing safer, more reliable autonomous detection systems. His work remains a foundational reference for engineers and researchers working on sensor fusion for buried threat detection, showcasing a clear pathway from algorithmic theory to real-world robotic deployment.
Research Focus
Key Achievements
Top Papers
- 1