Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares
about
Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis.Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.Adjudicating between face-coding models with individual-face fMRI responses.Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.Bottom-up and top-down computations in word- and face-selective cortex.Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments.On the partnership between neural representations of object categories and visual features in the ventral visual pathway.Visual search for object categories is predicted by the representational architecture of high-level visual cortex.
P2860
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P2860
Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares
description
2015 nî lūn-bûn
@nan
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
2015年论文
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2015年论文
@zh-cn
name
Visual features as stepping st ...... ith non-negative least squares
@ast
Visual features as stepping st ...... ith non-negative least squares
@en
type
label
Visual features as stepping st ...... ith non-negative least squares
@ast
Visual features as stepping st ...... ith non-negative least squares
@en
prefLabel
Visual features as stepping st ...... ith non-negative least squares
@ast
Visual features as stepping st ...... ith non-negative least squares
@en
P2093
P2860
P1433
P1476
Visual features as stepping st ...... ith non-negative least squares
@en
P2093
Kamila M Jozwik
Marieke Mur
Nikolaus Kriegeskorte
P2860
P304
P356
10.1016/J.NEUROPSYCHOLOGIA.2015.10.023
P577
2015-10-19T00:00:00Z