activity
20202022
most citedMEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy

16 citations · 41 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV202216 cited

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…

cs.CV20223 cited

Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition

Taehyeon Kim, Shinhwan Kang, Hyeonjeong Shin +4

The Weather4Cast competition (hosted by NeurIPS 2022) required competitors to predict super-resolution rain movies in various regions of Europe when low-resolution satellite contex…

cs.LG2022

Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels

Sumyeong Ahn, Se-Young Yun

Improperly constructed datasets can result in inaccurate inferences. For instance, models trained on biased datasets perform poorly in terms of generalization (i.e., dataset bias).…

cs.CL2022

Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks

Jaehoon Oh, Jongwoo Ko, Se-Young Yun

Translation has played a crucial role in improving the performance on multilingual tasks: (1) to generate the target language data from the source language data for training and (2…

cs.LG20223 cited

Neural Processes with Stochastic Attention: Paying more attention to the context dataset

Mingyu Kim, Kyeongryeol Go, Se-Young Yun

Neural processes (NPs) aim to stochastically complete unseen data points based on a given context dataset. NPs essentially leverage a given dataset as a context representation to d…

cs.LG202114 cited

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation

Taehyeon Kim, Jaehoon Oh, NakYil Kim +2

Knowledge distillation (KD), transferring knowledge from a cumbersome teacher model to a lightweight student model, has been investigated to design efficient neural architectures.…