Soopil Kim

According to our database, Soopil Kim authored at least 21 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Subject-adaptive meta-learning for personalized BCI: A fusion of resting-state EEG signal and task-specific information.

Sion An, Myeongkyun Kang, Soopil Kim, Philip Chikontwe, Li Shen, Sang Hyun Park

Inf. Fusion, 2026

2025

Communication Efficient Federated Learning for Multi-Organ Segmentation via Knowledge Distillation With Image Synthesis.

Soopil Kim, Heejung Park, Philip Chikontwe, Myeongkyun Kang, Kyong Hwan Jin, Ehsan Adeli, Kilian M. Pohl, Sang Hyun Park

IEEE Trans. Medical Imaging, May, 2025

Efficient one-shot federated learning on medical data using knowledge distillation with image synthesis and client model adaptation.

Myeongkyun Kang, Philip Chikontwe, Soopil Kim, Kyong Hwan Jin, Ehsan Adeli, Kilian M. Pohl, Sanghyun Park

Medical Image Anal., 2025

Revisiting Masked Image Modeling with Standardized Color Space for Domain Generalized Fundus Photography Classification.

Eojin Jang, Myeongkyun Kang, Soopil Kim, Min Sagong, Sang Hyun Park

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

Logical Anomaly Detection with Text-based Logic via Component-Aware Contrastive Language-Image Training.

Seung-eon Lee, Soopil Kim, Sion An, Sang-Chul Lee, Sang Hyun Park

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

MC-NuSeg: Multi-Contour Aware Nuclei Instance Segmentation with Segment Anything Model.

Hyun Namgung, Siwoo Nam, Soopil Kim, Sang Hyun Park

Proceedings of the Information Processing in Medical Imaging, 2025

2024

Dual Attention Relation Network With Fine-Tuning for Few-Shot EEG Motor Imagery Classification.

Sion An, Soopil Kim, Philip Chikontwe, Sanghyun Park

IEEE Trans. Neural Networks Learn. Syst., November, 2024

FedNN: Federated learning on concept drift data using weight and adaptive group normalizations.

Myeongkyun Kang, Soopil Kim, Kyong Hwan Jin, Ehsan Adeli, Kilian M. Pohl, Sanghyun Park

Pattern Recognit., 2024

Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets.

Soopil Kim, Heejung Park, Myeongkyun Kang, Kyong Hwan Jin, Ehsan Adeli, Kilian M. Pohl, Sanghyun Park

Medical Image Anal., 2024

Few-shot anomaly detection using positive unlabeled learning with cycle consistency and co-occurrence features.

Sion An, Jaehong Kim, Soopil Kim, Philip Chikontwe, Jiwook Jung, Hyejeong Jeon, Sang Hyun Park

Expert Syst. Appl., 2024

InstaSAM: Instance-Aware Segment Any Nuclei Model with Point Annotations.

Siwoo Nam, Hyun Namgung, Jaehoon Jeong, Miguel Luna, Soopil Kim, Philip Chikontwe, Sanghyun Park

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification.

Sion An, Myeongkyun Kang, Soopil Kim, Philip Chikontwe, Li Shen, Sang Hyun Park

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection.

Soopil Kim, Sion An, Philip Chikontwe, Myeongkyun Kang, Ehsan Adeli, Kilian M. Pohl, Sanghyun Park

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Uncertainty-aware semi-supervised few shot segmentation.

Soopil Kim, Philip Chikontwe, Sion An, Sanghyun Park

Pattern Recognit., May, 2023

One-Shot Federated Learning on Medical Data Using Knowledge Distillation with Image Synthesis and Client Model Adaptation.

Myeongkyun Kang, Philip Chikontwe, Soopil Kim, Kyong Hwan Jin, Ehsan Adeli-Mosabbeb, Kilian M. Pohl, Sanghyun Park

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022

A Meta-Learning Approach for Medical Image Registration.

Heejung Park, Gyeong Min Lee, Soopil Kim, Ga Hyung Ryu, Areum Jeong, Min Sagong, Sang Hyun Park

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification.

Philip Chikontwe, Soopil Kim, Sang Hyun Park

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Uncertainty-Aware Semi-Supervised Few Shot Segmentation.

Soopil Kim, Philip Chikontwe, Sang Hyun Park

CoRR, 2021

Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation.

Soopil Kim, Sion An, Philip Chikontwe, Sang Hyun Park

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Few-Shot Relation Learning with Attention for EEG-based Motor Imagery Classification.

Sion An, Soopil Kim, Philip Chikontwe, Sang Hyun Park

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2019

Two-Step U-Nets for Brain Tumor Segmentation and Random Forest with Radiomics for Survival Time Prediction.

Soopil Kim, Miguel Luna, Philip Chikontwe, Sang Hyun Park

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019