Tae Hyung Kim

Orcid: 0000-0001-5881-7265

Affiliations:
  • Hongik University, Department of Computer Engineering, Seoul, Korea
  • Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA (2020-2022)
  • University of Southern California, Signal and Image Processing Institute, Los Angeles, CA, US (PhD 2020)


According to our database1, Tae Hyung Kim authored at least 17 papers between 2015 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2025
ZIUM: Zero-Shot Intent-Aware Adversarial Attack on Unlearned Models.
CoRR, July, 2025

Zero-Shot Recon2Recon: Data-Free Unsupervised Denoiser Learning for Plug-and-Play Magnetic Resonance Imaging Reconstruction.
IEEE Access, 2025

2024
Orthogonal Transform-Driven Data Augmentation for Limited Gaussian-Tainted Dataset.
IEEE Access, 2024

Enhanced Partial Fourier MRI With Zero-Shot Deep Untrained Priors.
IEEE Access, 2024

To Detect, and Beyond: Integrating Text-Guided Object Detection and Super-Resolution.
Proceedings of the 15th International Conference on Information and Communication Technology Convergence, 2024

Composition-based Detail Preservation in Pose Transformation Using Diffusion Models.
Proceedings of the 15th International Conference on Information and Communication Technology Convergence, 2024

2023
High-fidelity mesoscale in-vivo diffusion MRI through gSlider-BUDA and circular EPI with S-LORAKS reconstruction.
NeuroImage, 2023

Enhancing Nighttime Vehicle Detection via Transformer-based Data Augmentation.
Proceedings of the 14th International Conference on Information and Communication Technology Convergence, 2023

2022
Wave-Encoded Model-based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction.
CoRR, 2022

2021
Accurate parameter estimation using scan-specific unsupervised deep learning for relaxometry and MR fingerprinting.
CoRR, 2021

2020
Efficient Iterative Solutions to Complex-Valued Nonlinear Least-Squares Problems with Mixed Linear and Antilinear Operators.
CoRR, 2020

2019
LORAKI: Autocalibrated Recurrent Neural Networks for Autoregressive MRI Reconstruction in k-Space.
CoRR, 2019

Learning How to Interpolate Fourier Data With Unknown Autoregressive Structure: An Ensemble-Based Approach.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Navigator-Free EPI Ghost Correction With Structured Low-Rank Matrix Models: New Theory and Methods.
IEEE Trans. Medical Imaging, 2018

The Fourier radial error spectrum plot: A more nuanced quantitative evaluation of image reconstruction quality.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Computational imaging with loraks: Reconstructing linearly predictable signals using low-rank matrix regularization.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2015
SMS-LORAKS: Calibrationless simultaneous multislice MRI using low-rank matrix modeling.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015


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