4 citations · 7 across the 3 of their papers we have counts for
4 papers
Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout
Pengfei Xie, Linyuan Wang, Ruoxi Qin +4
Deep neural networks(DNNs) is vulnerable to be attacked by adversarial examples. Black-box attack is the most threatening attack. At present, black-box attack methods mainly adopt…
Dual-energy CT Reconstruction from Dual Quarter Scans
Wenkun Zhang, Ningning Liang, Linyuan Wang +7
Compared with conventional single-energy computed tomography (CT), dual-energy CT (DECT) provides better material differentiation but most DECT imaging systems require dual full-an…
A visual encoding model based on deep neural networks and transfer learning
Chi Zhang, Kai Qiao, Linyuan Wang +4
Background: Building visual encoding models to accurately predict visual responses is a central challenge for current vision-based brain-machine interface techniques. To achieve hi…
Dissociable neural representations of adversarially perturbed images in convolutional neural networks and the human brain
Chi Zhang, Xiaohan Duan, Linyuan Wang +5
Despite the remarkable similarities between convolutional neural networks (CNN) and the human brain, CNNs still fall behind humans in many visual tasks, indicating that there still…