21 citations · 57 across the 5 of their papers we have counts for
8 papers
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…
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…
Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
Cheng Peng, Wei-An Lin, Haofu Liao +2
We propose a marginal super-resolution (MSR) approach based on 2D convolutional neural networks (CNNs) for interpolating an anisotropic brain magnetic resonance scan along the high…
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Haofu Liao, Wei-An Lin, S. Kevin Zhou +1
Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training…