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Dive into the research topics where Young Doo Son is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Artificial intelligence-enhanced diagnosis of degenerative joint disease using temporomandibular joint panoramic radiography and joint noise data
Choi, E., Shin, S., Lee, K., An, T., Lee, R. K., Kim, S., Son, Y. & Kim, S. T., Dec 2025, In: Scientific Reports. 15, 1, 1823.Research output: Contribution to journal › Article › peer-review
Open Access9 Scopus citations -
Batch active learning for time-series classification with multi-mode exploration
Lee, S., Choi, C., Do, H. & Son, Y., Sep 2025, In: Information Sciences. 711, 122109.Research output: Contribution to journal › Article › peer-review
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Black-box adversarial examples via frequency distortion against fault diagnosis systems
Lee, S., Kim, H., Lee, W. & Son, Y., Mar 2025, In: Applied Soft Computing. 171, 112828.Research output: Contribution to journal › Article › peer-review
3 Scopus citations -
Correction to: Artificial intelligence-enhanced diagnosis of degenerative joint disease using temporomandibular joint panoramic radiography and joint noise data (Scientific Reports, (2025), 15, 1, (1823), 10.1038/s41598-024-83750-4)
Choi, E., Shin, S., Lee, K., An, T., Lee, R. K., Kim, S., Son, Y. & Kim, S. T., Dec 2025, In: Scientific Reports. 15, 1, 12797.Research output: Contribution to journal › Comment/debate
Open Access -
Homomorphic encryption-based fault diagnosis in IoT-enabled industrial systems
Kim, H., Son, Y. & Byun, J., Jun 2025, In: International Journal of Information Security. 24, 3, 102.Research output: Contribution to journal › Article › peer-review
Press/Media
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Findings from Dongguk University Seoul Reveals New Findings on Information Technology (Multi-stage Ensemble With Refinement for Noisy Labeled Data Classification)
28/11/24
1 item of Media coverage
Press/Media
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Studies from Dongguk University Seoul in the Area of Technology Reported (Relation-preserving Masked Modeling for Semi-supervised Time-series Classification)
4/10/24
1 item of Media coverage
Press/Media