ksoh97
Graduate Student, Department of Artificial Intelligence, Korea University
@ku-milabSeoul, South Korea
ksoh97's Stars
qubvel/segmentation_models
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
rishigami/Swin-Transformer-TF
Tensorflow implementation of Swin Transformer model.
mazurowski-lab/segment-anything-medical-evaluation
Code for "Segment Anything Model for Medical Image Analysis: an Experimental Study" in Medical Image Analysis
yuhoo0302/Segment-Anything-Model-for-Medical-Images
Codes and models for Medical Image Analysis (MIA) 2023 paper. Segment Anything Model for Medical Images?.
cheng-01037/Causality-Medical-Image-Domain-Generalization
[IEEE-TMI'22] Causality-inspired Single-source Domain Generalization for Medical Image Segmentation (code&data-processing pipeline)
Kaiseem/SLAug
[AAAI 2023] Official PyTorch implementation of the paper "SLAug: Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation"
seuzjj/Diffusion_kernel_attention_network
wko1014/VIGNet
A source code for "VIGNet: A deep convolutional neural network for EEG-based driver vigilance estiamtion"
ksoh97/Driver-drowsiness-classification
Mini-project using the PyTorch framework
wko1014/EOSSL_CAA
Self-supervised spatio-spectro-temporal represenation learning for EEG analysis
awmulyadi/XADLiME
We propose a novel deep-learning approach through eXplainable AD Likelihood Map Estimation (XADLiME) for AD progression modeling over 3D sMRIs using clinically-guided prototype learning
ejjun92/VRNN_GRU-U
ku-milab/LiCoL
ku-milab/GMBA
Pytorch implementation of "Age-Aware Guidance via Masking-Based Attention in Face Aging" [CIKM 2023]
ku-milab/XADLiME
We propose a novel deep-learning approach through eXplainable AD Likelihood Map Estimation (XADLiME) for AD progression modeling over 3D sMRIs using clinically-guided prototype learning
ksoh97/FIESTA
Pytorch implementation of "FIESTA: Fourier-based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation" [Submitted to MedIA]
ksoh97/ksoh97
ksoh97/MelGAN-Waveform-synthesis
Pytorch re-implementation of MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis.
ksoh97/Brain-tumor-segmentation
Mini-project using the TensorFlow and PyTorch framework jointly
ksoh97/gala_tpu
ksoh97/innvestigate
A toolbox to iNNvestigate neural networks' predictions!
ksoh97/interpretable-ml-book
Book about interpretable machine learning
ksoh97/LiCoL
Tensorflow implementation of "A Quantitatively Interpretable Model for Alzheimer’s Disease Prediction Using Deep Counterfactuals" [MedNeurIPS2022], [Submitted to TPAMI]
ksoh97/scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
ksoh97/segmentation_models
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
ksoh97/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]
ksoh97/VIGNet
A source code for "VIGNet: A deep convolutional neural network for EEG-based driver vigilance estiamtion"
ksoh97/xai_resources
Interesting resources related to XAI (Explainable Artificial Intelligence)
ku-milab/FIESTA
ku-milab/UHF-guided_segmentation
PyTorch implementation of "Transferring Ultra-high Field Representations for Intensity-Guided Brain Segmentation of Low Field MRI"