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Matches in SemOpenAlex for { <https://semopenalex.org/work/W2002476095> ?p ?o ?g. }

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• W2002476095 startingPage "12046" @default.
• W2002476095 abstract "Efficient and reliable classification of visual stimuli requires that their representations reside a low-dimensional and, therefore, computationally manageable feature space. We investigated the ability of the human visual system to derive such representations from the sensory input-a highly nontrivial task, given the million or so dimensions of the visual signal at its entry point to the cortex. In a series of experiments, subjects were presented with sets of parametrically defined shapes; the points in the common high-dimensional parameter space corresponding to the individual shapes formed regular planar (two-dimensional) patterns such as a triangle, a square, etc. We then used multidimensional scaling to arrange the shapes in planar configurations, dictated by their experimentally determined perceived similarities. The resulting configurations closely resembled the original arrangements of the stimuli in the parameter space. This achievement of the human visual system was replicated by a computational model derived from a theory of object representation in the brain, according to which similarities between objects, and not the geometry of each object, need to be faithfully represented." @default.
• W2002476095 created "2016-06-24" @default.
• W2002476095 creator A5007763032 @default.
• W2002476095 creator A5049585835 @default.
• W2002476095 date "1996-10-15" @default.
• W2002476095 modified "2023-10-04" @default.
• W2002476095 title "Faithful representation of similarities among three-dimensional shapes in human vision." @default.
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• W2002476095 doi "https://doi.org/10.1073/pnas.93.21.12046" @default.
• W2002476095 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/38180" @default.
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