Sanghyun Seo
Papers
2
Total Citations
121
H-Index
2
About
Dr. Sanghyun Seo is a researcher specializing in deep learning, computer vision, and medical image analysis. His primary contributions lie in developing efficient neural network architectures for human action recognition and exploring machine learning applications in ophthalmology. His most impactful work, "A resource conscious human action recognition framework using 26-layered deep convolutional neural network" (2020, 105 citations), introduces a computationally efficient deep learning model that balances accuracy with resource constraints, making it suitable for real-time applications. This framework has been widely referenced in the field of action recognition and embedded vision systems. Dr. Seo has also investigated automated medical diagnostics, including a study on glaucoma progression detection using K-means clustering and GLCM algorithms, though this work was later retracted. Despite this, his broader research demonstrates a commitment to bridging deep learning with practical, resource-aware solutions. With over 100 citations on his leading paper, Dr. Seo’s work continues to influence the development of efficient AI models for both human-centered computing and biomedical applications.
Research Focus
Key Achievements
Top Papers
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