3 citations · 9 across the 9 of their papers we have counts for
5 papers · 1 filter
Intrinsic Bias Identification on Medical Image Datasets
Shijie Zhang, Lanjun Wang, Lian Ding +3
Machine learning based medical image analysis highly depends on datasets. Biases in the dataset can be learned by the model and degrade the generalizability of the applications. Th…
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation
Saeed Ranjbar Alvar, Lanjun Wang, Jian Pei +1
Image-to-image translation models are shown to be vulnerable to the Membership Inference Attack (MIA), in which the adversary's goal is to identify whether a sample is used to trai…
Finding Representative Interpretations on Convolutional Neural Networks
Peter Cho-Ho Lam, Lingyang Chu, Maxim Torgonskiy +3
Interpreting the decision logic behind effective deep convolutional neural networks (CNN) on images complements the success of deep learning models. However, the existing methods c…
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification
Yongwei Wang, Mingquan Feng, Rabab Ward +2
Deep neural networks are vulnerable to adversarial attacks. White-box adversarial attacks can fool neural networks with small adversarial perturbations, especially for large size i…
Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution
Lingyang Chu, Xia Hu, Juhua Hu +2
Strong intelligent machines powered by deep neural networks are increasingly deployed as black boxes to make decisions in risk-sensitive domains, such as finance and medical. To re…