58 citations · 151 across the 19 of their papers we have counts for
6 papers · 1 filter
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…
Decoding visual stimuli in human brain by using Anatomical Pattern Analysis on fMRI images
Muhammad Yousefnezhad, Daoqiang Zhang
A universal unanswered question in neuroscience and machine learning is whether computers can decode the patterns of the human brain. Multi-Voxels Pattern Analysis (MVPA) is a crit…
Weighted Spectral Cluster Ensemble
Muhammad Yousefnezhad, Daoqiang Zhang
Clustering explores meaningful patterns in the non-labeled data sets. Cluster Ensemble Selection (CES) is a new approach, which can combine individual clustering results for increa…