8 citations · 29 across the 12 of their papers we have counts for
4 papers · 1 filter
Fast Local Attack: Generating Local Adversarial Examples for Object Detectors
Quanyu Liao, Xin Wang, Bin Kong +4
The deep neural network is vulnerable to adversarial examples. Adding imperceptible adversarial perturbations to images is enough to make them fail. Most existing research focuses…
Graph Neural Networks for UnsupervisedDomain Adaptation of Histopathological ImageAnalytics
Dou Xu, Chang Cai, Chaowei Fang +3
Annotating histopathological images is a time-consuming andlabor-intensive process, which requires broad-certificated pathologistscarefully examining large-scale whole-slide images…
Category-wise Attack: Transferable Adversarial Examples for Anchor Free Object Detection
Quanyu Liao, Xin Wang, Bin Kong +4
Deep neural networks have been demonstrated to be vulnerable to adversarial attacks: subtle perturbations can completely change the classification results. Their vulnerability has…
Domain Embedded Multi-model Generative Adversarial Networks for Image-based Face Inpainting
Xian Zhang, Xin Wang, Bin Kong +6
Prior knowledge of face shape and structure plays an important role in face inpainting. However, traditional face inpainting methods mainly focus on the generated image resolution…