5 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 5 cited
ReConPatch : Contrastive Patch Representation Learning for Industrial Anomaly Detection
Jeeho Hyun, Sangyun Kim, Giyoung Jeon +3
Anomaly detection is crucial to the advanced identification of product defects such as incorrect parts, misaligned components, and damages in industrial manufacturing. Due to the r…
cs.LG2022
On the Relationship Between Adversarial Robustness and Decision Region in Deep Neural Networks
Seongjin Park, Haedong Jeong, Tair Djanibekov +3
In general, Deep Neural Networks (DNNs) are evaluated by the generalization performance measured on unseen data excluded from the training phase. Along with the development of DNNs…
cs.LG2019★ 3 cited
An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks
Giyoung Jeon, Haedong Jeong, Jaesik Choi
Deep generative neural networks (DGNNs) have achieved realistic and high-quality data generation. In particular, the adversarial training scheme has been applied to many DGNNs and…