activity
20162023
most citedLess-forgetting Learning in Deep Neural Networks

162 citations · 167 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2023

Semantic Map Guided Synthesis of Wireless Capsule Endoscopy Images using Diffusion Models

Haejin Lee, Jeongwoo Ju, Jonghyuck Lee +2

Wireless capsule endoscopy (WCE) is a non-invasive method for visualizing the gastrointestinal (GI) tract, crucial for diagnosing GI tract diseases. However, interpreting WCE resul…

cs.CV2021★ 2 cited

Rethinking Query, Key, and Value Embedding in Vision Transformer under Tiny Model Constraints

Jaesin Ahn, Jiuk Hong, Jeongwoo Ju +1

A vision transformer (ViT) is the dominant model in the computer vision field. Despite numerous studies that mainly focus on dealing with inductive bias and complexity, there remai…

cs.LG2021

Extending Contrastive Learning to Unsupervised Coreset Selection

Jeongwoo Ju, Heechul Jung, Yoonju Oh +1

Self-supervised contrastive learning offers a means of learning informative features from a pool of unlabeled data. In this paper, we delve into another useful approach -- providin…

cs.LG2017★ 3 cited

Less-forgetful Learning for Domain Expansion in Deep Neural Networks

Heechul Jung, Jeongwoo Ju, Minju Jung +1

Expanding the domain that deep neural network has already learned without accessing old domain data is a challenging task because deep neural networks forget previously learned inf…

cs.LG2016★ 162 cited

Less-forgetting Learning in Deep Neural Networks

Heechul Jung, Jeongwoo Ju, Minju Jung +1

A catastrophic forgetting problem makes deep neural networks forget the previously learned information, when learning data collected in new environments, such as by different senso…