58 citations · 81 across the 10 of their papers we have counts for
7 papers
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack
Mengting Xu, Tao Zhang, Zhongnian Li +2
Deep learning models (with neural networks) have been widely used in challenging tasks such as computer-aided disease diagnosis based on medical images. Recent studies have shown d…
SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction
Zhongnian Li, Tao Zhang, Peng Wan +1
Generative Adversarial Networks (GANs) are powerful tools for reconstructing Compressed Sensing Magnetic Resonance Imaging (CS-MRI). However most recent works lack exploration of s…
Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains
Muhammad Yousefnezhad, Daoqiang Zhang
Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. There is a wide range of c…
WoCE: a framework for clustering ensemble by exploiting the wisdom of Crowds theory
Muhammad Yousefnezhad, Sheng-Jun Huang, Daoqiang Zhang
The Wisdom of Crowds (WOC), as a theory in the social science, gets a new paradigm in computer science. The WOC theory explains that the aggregate decision made by a group is often…
Local Discriminant Hyperalignment for multi-subject fMRI data alignment
Muhammad Yousefnezhad, Daoqiang Zhang
Multivariate Pattern (MVP) classification can map different cognitive states to the brain tasks. One of the main challenges in MVP analysis is validating the generated results acro…
A new selection strategy for selective cluster ensemble based on Diversity and Independency
Muhammad Yousefnezhad, Ali Reihanian, Daoqiang Zhang +1
This research introduces a new strategy in cluster ensemble selection by using Independency and Diversity metrics. In recent years, Diversity and Quality, which are two metrics in…