22 citations · 40 across the 5 of their papers we have counts for
3 papers · 1 filter
Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation
Hong Joo Lee, Seong Tae Kim, Hakmin Lee +2
Recent studies have shown that ensemble approaches could not only improve accuracy and but also estimate model uncertainty in deep learning. However, it requires a large number of…
Revisiting Role of Autoencoders in Adversarial Settings
Byeong Cheon Kim, Jung Uk Kim, Hakmin Lee +1
To combat against adversarial attacks, autoencoder structure is widely used to perform denoising which is regarded as gradient masking. In this paper, we revisit the role of autoen…
Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack
Hakmin Lee, Hong Joo Lee, Seong Tae Kim +1
Deep neural networks have achieved substantial achievements in several computer vision areas, but have vulnerabilities that are often fooled by adversarial examples that are not re…