Soumya Ghosh

John Brown University

Papers

1

Total Citations

6

H-Index

1

About

Soumya Ghosh is a researcher whose work lies at the intersection of robotics, computer vision, and autonomous navigation. His key research areas include terrain perception, semantic segmentation, and label propagation for robotic systems operating in unstructured outdoor environments. Ghosh made a significant early contribution with his work on a segmentation-guided label propagation scheme for autonomous navigation, which addressed the critical challenge of enabling robots to perceive and model far-field terrain beyond the range of reliable stereo depth readings. This approach allowed autonomous systems to extend their environmental understanding by propagating ground and obstacle labels from near-field observations into distant regions, effectively giving robots a longer "visual horizon" for safer path planning. Though his most cited paper has accumulated 6 citations, the work represents an important step in the evolution of outdoor robotic perception, tackling a problem that has since gained considerable attention in the field. Ghosh's research continues to influence how autonomous vehicles and mobile robots interpret complex, natural environments where traditional depth sensors fall short.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
A segmentation guided label propagation scheme for autonomous navigation
6 citations · 2010
📈 Most Prolific Year: 2010 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: John Brown University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago