27 citations · 35 across the 5 of their papers we have counts for
5 papers
LEAT: Towards Robust Deepfake Disruption in Real-World Scenarios via Latent Ensemble Attack
Joonkyo Shim, Hyunsoo Yoon
Deepfakes, malicious visual contents created by generative models, pose an increasingly harmful threat to society. To proactively mitigate deepfake damages, recent studies have emp…
UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly Detection
Yujin Lee, Harin Lim, Seoyoon Jang +1
Visual anomaly detection aims to learn normality from normal images, but existing approaches are fragmented across various tasks: defect detection, semantic anomaly detection, mult…
AVATAR: Adversarial self-superVised domain Adaptation network for TARget domain
Jun Kataoka, Hyunsoo Yoon
This paper presents an unsupervised domain adaptation (UDA) method for predicting unlabeled target domain data, specific to complex UDA tasks where the domain gap is significant. M…
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation
Firas Al-Hindawi, Tejaswi Soori, Han Hu +4
The detection of critical heat flux (CHF) is crucial in heat boiling applications as failure to do so can cause rapid temperature ramp leading to device failures. Many machine lear…
A Feature Transfer Enabled Multi-Task Deep Learning Model on Medical Imaging
Fei Gao, Hyunsoo Yoon, Teresa Wu +1
Object detection, segmentation and classification are three common tasks in medical image analysis. Multi-task deep learning (MTL) tackles these three tasks jointly, which provides…