Seungmin Rho

Chung-Ang University, Sungkyul University

Papers

Total Citations

H-Index

About

Dr. Seungmin Rho is a leading researcher in computer vision and human action recognition, with a focus on deep learning and transfer learning approaches. His most impactful work, "A transfer learning-based efficient spatiotemporal human action recognition framework for long and overlapping action classes" (2021, 48 citations), addresses a critical challenge in video understanding: accurately identifying complex, prolonged, and overlapping human actions. By leveraging transfer learning, Dr. Rho’s framework significantly improves computational efficiency and recognition accuracy, making it highly applicable to surveillance, human-computer interaction, and sports analytics. He has also made notable contributions to depth estimation from single monocular images, as demonstrated in his 2016 work (18 citations), where he developed a deep hybrid network that enhances spatial understanding for autonomous systems and augmented reality. Dr. Rho’s research bridges theoretical advances in deep learning with practical, real-world applications, earning him recognition for tackling some of the most difficult problems in spatiotemporal analysis. His work continues to influence the development of robust, scalable AI systems for dynamic visual environments.