Kang, M., Kaji, S., Lee, S. Y., Kim, T., Ryu, H. H., & Choi, S. (2025). Shape-Aware Topological Representation for Pipeline Hyperbola Detection in GPR Data. IEEE Sensors Journal, vol. 26, no. 3, pp. 4313--4325, 2026. https://doi.org/10.1109/JSEN.2025.3642308, arXiv:2506.06311
Ryu, H. H., Choi, S., Chong, S. H., Kim, T. Y., Lee, J., & Kang, M. (2025). Machine learning-based prediction of underground utility counts using electrical resistance numerical data. Geomechanics & engineering, vol.41, no.1, pp.11-19. https://doi.org/10.12989/gae.2025.41.1.011
Lee, J., Kim, K., Kang, M., Hong, E. S., & Choi, S. (2024). Void detection for tunnel lining backfill using impact-echo method based on continuous wavelet transform and convolutional neural network.Geomechanics & engineering, vol36, no.1, pp.1-8. https://doi.org/10.12989/gae.2024.39.1.105
Kim, T. Y., Ryu, H. H., Kang, M., Choi, S., & Chong, S. H. (2024). Effect of geometry of underground structure and electrode on electrical resistance measurement: A numerical study. Geomechanics & engineering, vol39, no.1, pp.105-113. https://doi.org/10.12989/gae.2024.39.1.105
Ryu, H. H., Choi, S., Chong, S. H., Kim, T. Y., Lee, J., & Kang, M. Machine learning-based classification of underground utility counts using electrical resistance numerical module.
Outstanding Thesis Award (Bronze), BK21 Phase 4 Program, Ajou University, 2025
“Shape-Aware Topological Representation for Pipeline Hyperbola Detection in GPR Data”