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@ku-milab

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ksoh97/README.md

Kwanseok Oh (Kwan Seok Oh)

I am an integrated M.S/Ph.D student of Artificial Intelligence, Korea University.

Contact

Research Interest

  • Machine/Deep learning, Computer vision, Explainable AI, and Biomedical image analysis

Skill

  • Programming Language: Python, Visual C/C++, Javascript, R, and MATLAB
  • Deep Learning Framework: TensorFlow/Keras, PyTorch

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  1. LEAR LEAR Public

    Tensorflow implementation of "Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model" [TPAMI 2023]

    Python 6 1

  2. LiCoL LiCoL Public

    Forked from ku-milab/LiCoL

    Tensorflow implementation of "A Quantitatively Interpretable Model for Alzheimer’s Disease Prediction Using Deep Counterfactuals" [MedNeurIPS2022], [Submitted to TPAMI]

    Python 1

  3. UHF-guided_segmentation UHF-guided_segmentation Public

    Forked from ku-milab/UHF-guided_segmentation

    PyTorch implementation of "Transferring Ultra-high Field Representations for Intensity-Guided Brain Segmentation of Low Field MRI" [MICCAI 2022], [Submitted to MedIA]

    Python 1

  4. GMBA GMBA Public

    Forked from ku-milab/GMBA

    Pytorch implementation of "Age-Aware Guidance via Masking-Based Attention in Face Aging" [CIKM 2023]

    Python

  5. FIESTA FIESTA Public

    Pytorch implementation of "FIESTA: Fourier-based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation" [Submitted to MedIA]

    Python 2 1

  6. BIN BIN Public

    Tensorflow implementation of "Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision"

    Python 6