Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.
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Category-Selectivity in Human Visual Cortex Follows Cortical Topology: A Grouped icEEG StudyNeurophysiological Organization of the Middle Face Patch in Macaque Inferior Temporal CortexLinear and Non-Linear Visual Feature Learning in Rat and Humans.Using goal-driven deep learning models to understand sensory cortex.Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing.Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition.Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.Explicit information for category-orthogonal object properties increases along the ventral stream.
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Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.
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name
Simple Learned Weighted Sums o ...... bject Recognition Performance.
@ast
Simple Learned Weighted Sums o ...... bject Recognition Performance.
@en
type
label
Simple Learned Weighted Sums o ...... bject Recognition Performance.
@ast
Simple Learned Weighted Sums o ...... bject Recognition Performance.
@en
prefLabel
Simple Learned Weighted Sums o ...... bject Recognition Performance.
@ast
Simple Learned Weighted Sums o ...... bject Recognition Performance.
@en
P2093
P2860
P50
P1476
Simple Learned Weighted Sums o ...... Object Recognition Performance
@en
P2093
Ethan A Solomon
James J DiCarlo
Najib J Majaj
P2860
P304
13402-13418
P356
10.1523/JNEUROSCI.5181-14.2015
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P577
2015-09-01T00:00:00Z