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A high-throughput screening approach to discovering good forms of biologically inspired visual representation

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title

A high-throughput screening approach to discovering good forms of biologically inspired visual representation (English)

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main subject

high-throughput screening

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3

James J DiCarlo

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author name string

Nicolas Pinto

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1

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David Doukhan

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2

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David D Cox

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4

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language of work or name

English

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publication date

November 2009

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published in

PLOS Computational Biology

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volume

5

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issue

11

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page(s)

e1000579

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copyright license

Creative Commons Attribution 4.0 International

start time

26 November 2009

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April 2022 Public Data File from Crossref

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copyrighted

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cites work

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Unsupervised natural experience rapidly alters invariant object representation in visual cortex

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reference URL

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A model of invariant object recognition in the visual system: learning rules, activation functions, lateral inhibition, and information-based performance measures.

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Robust object recognition with cortex-like mechanisms.

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A Survey of General-Purpose Computation on Graphics Hardware

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'Breaking' position-invariant object recognition

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Untangling invariant object recognition.

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21 January 2018

Learning viewpoint invariant object representations using a temporal coherence principle.

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Stimulus timing-dependent plasticity in cortical processing of orientation

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Distinctive Image Features from Scale-Invariant Keypoints

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Identifiers

DOI

10.1371/JOURNAL.PCBI.1000579

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DBLP publication ID

journals/ploscb/PintoDDC09

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stated in

DBLP Dataset 2021-01-02

28 January 2021

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ResearchGate publication ID

40443832

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(Q27335114)

A high-throughput screening approach to discovering good forms of biologically inspired visual representation

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