206 citations · 336 across the 12 of their papers we have counts for
12 papers
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses
Chun Pong Lau, Jiang Liu, Hossein Souri +3
Adversarial training (AT) is considered to be one of the most reliable defenses against adversarial attacks. However, models trained with AT sacrifice standard accuracy and do not…
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks
Wei-An Lin, Chun Pong Lau, Alexander Levine +2
Adversarial training is a popular defense strategy against attack threat models with bounded Lp norms. However, it often degrades the model performance on normal images and the def…
SAINT: Spatially Aware Interpolation NeTwork for Medical Slice Synthesis
Cheng Peng, Wei-An Lin, Haofu Liao +2
Deep learning-based single image super-resolution (SISR) methods face various challenges when applied to 3D medical volumetric data (i.e., CT and MR images) due to the high memory…
Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography
Yuanyuan Lyu, Wei-An Lin, Haofu Liao +2
Metal artifact reduction (MAR) in computed tomography (CT) is a notoriously challenging task because the artifacts are structured and non-local in the image domain. However, they a…
Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference
Wei-An Lin, Yogesh Balaji, Pouya Samangouei +1
Inferring the latent variable generating a given test sample is a challenging problem in Generative Adversarial Networks (GANs). In this paper, we propose InvGAN - a novel framewor…
Towards multi-sequence MR image recovery from undersampled k-space data
Cheng Peng, Wei-An Lin, Rama Chellappa +1
Undersampled MR image recovery has been widely studied for accelerated MR acquisition. However, it has been mostly studied under a single sequence scenario, despite the fact that m…