Shinhye Yun

Purdue University West Lafayette

Papers

1

Total Citations

2

H-Index

1

About

Shinhye Yun is a researcher advancing the intersection of computer vision and autonomous robotics, with a focus on enabling intelligent systems to perceive and navigate their environments. Their most cited work, "Target Distance Calculation Method Using Image Segmentation" (2020), introduces a novel approach that leverages image segmentation to allow robots to accurately calculate distances to targets, a critical capability for autonomous operation in hazardous environments where human presence is risky. This contribution addresses the growing demand for cost-effective, high-performance robotic systems that can replace human labor in dangerous settings. While early in their career, Yun’s research has already garnered attention, with the paper accumulating 2 citations, signaling its relevance to peers working on robotic perception and safety. By combining hardware and software innovations, Yun is helping to design systems that not only enhance efficiency but also protect human life, marking them as a promising voice in the fields of image processing and robotics. Their work lays a foundation for future advancements in autonomous navigation and human-robot interaction.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Target Distance Calculation Method Using Image Segmentation
2 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Purdue University West Lafayette

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago