Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.
about
Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis.Adjudicating between face-coding models with individual-face fMRI responses.Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.Constraint-Free Natural Image Reconstruction From fMRI Signals Based on Convolutional Neural Network.
P2860
Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.
description
2017 nî lūn-bûn
@nan
2017年の論文
@ja
2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
2017年论文
@zh
2017年论文
@zh-cn
name
Fixed versus mixed RSA: Explai ...... and deep computational models.
@en
type
label
Fixed versus mixed RSA: Explai ...... and deep computational models.
@en
prefLabel
Fixed versus mixed RSA: Explai ...... and deep computational models.
@en
P2860
P50
P1476
Fixed versus mixed RSA: Explai ...... and deep computational models.
@en
P2093
Nikolaus Kriegeskorte
P2860
P304
P356
10.1016/J.JMP.2016.10.007
P577
2017-02-01T00:00:00Z