53 citations · 70 across the 3 of their papers we have counts for
4 papers
FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning
Seongyoon Kim, Gihun Lee, Jaehoon Oh +1
Federated Learning (FL) is a collaborative method for training models while preserving data privacy in decentralized settings. However, FL encounters challenges related to data het…
MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy
Gihun Lee, Sangmook Kim, Joonkee Kim +1
Cell segmentation is a fundamental task for computational biology analysis. Identifying the cell instances is often the first step in various downstream biomedical studies. However…
MixCo: Mix-up Contrastive Learning for Visual Representation
Sungnyun Kim, Gihun Lee, Sangmin Bae +1
Contrastive learning has shown remarkable results in recent self-supervised approaches for visual representation. By learning to contrast positive pairs' representation from the co…
SIPA: A Simple Framework for Efficient Networks
Gihun Lee, Sangmin Bae, Jaehoon Oh +1
With the success of deep learning in various fields and the advent of numerous Internet of Things (IoT) devices, it is essential to lighten models suitable for low-power devices. I…