Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties
about
Sample-poor estimation of order and common signal subspace with application to fusion of medical imaging data.Approaches to Capture Variance Differences in Rest fMRI Networks in the Spatial Geometric Features: Application to Schizophrenia.Quantifying the Interaction and Contribution of Multiple Datasets in Fusion: Application to the Detection of SchizophreniaOptimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.Mathematically universal and biologically consistent astrocytoma genotype encodes for transformation and predicts survival phenotype
P2860
Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties
description
2015 nî lūn-bûn
@nan
2015 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2015 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
name
Multi-modal data fusion using ...... A and IVA and their properties
@ast
Multi-modal data fusion using ...... A and IVA and their properties
@en
type
label
Multi-modal data fusion using ...... A and IVA and their properties
@ast
Multi-modal data fusion using ...... A and IVA and their properties
@en
prefLabel
Multi-modal data fusion using ...... A and IVA and their properties
@ast
Multi-modal data fusion using ...... A and IVA and their properties
@en
P2860
P50
P1476
Multi-modal data fusion using ...... A and IVA and their properties
@en
P2860
P304
P356
10.1109/JPROC.2015.2461624
P577
2015-09-01T00:00:00Z