Regularization with Multiple Feature Combination for Few-Shot Learning. - Su Been Lee; Jun Ho Park; Ji Young Kim; Seung Yeol Lee; Jae-Pil Heo (BigComp, 2021)

Evaluation of a Machine Learning Approach to Identify ADL Impairment in Clinical Notes of People with Dementia. - John Laurentiev; Mufaddal Mahesri; Lily G. Bessette; Cassandra York; Heidi Zakoul; Su Been Lee; Dae Hyun Kim; Li Zhou 007; Joshua Lin (AMIA, 2022)

Task Discrepancy Maximization for Fine-grained Few-Shot Classification. - Su Been Lee; WonJun Moon; Jae-Pil Heo (CVPR, 2022)

Leveraging Hidden Positives for Unsupervised Semantic Segmentation. - Hyun Seok Seong; WonJun Moon; Su Been Lee; Jae-Pil Heo (CVPR, 2023)

Task-Oriented Channel Attention for Fine-Grained Few-Shot Classification. - Su Been Lee; WonJun Moon; Hyun Seok Seong; Jae-Pil Heo (CoRR, 2023)

Correlation-guided Query-Dependency Calibration in Video Representation Learning for Temporal Grounding. - WonJun Moon; Sangeek Hyun; Su Been Lee; Jae-Pil Heo (CoRR, 2023)

Task-Disruptive Background Suppression for Few-Shot Segmentation. - Suho Park; Su Been Lee; Sangeek Hyun; Hyun Seok Seong; Jae-Pil Heo (AAAI, 2024)