Seeing patterns in the noise

Eero P. Simoncelli

doi:10.1016/S1364-6613(02)00043-8

Seeing patterns in the noise

Eero P. Simoncelli

Neural Science

Research output: Contribution to journal › Short survey › peer-review

Abstract

How do observers detect the presence of objects or features in visual images? Stochastic stimuli (for example, white noise) have become popular choices for providing a linear characterization of early sensory mechanisms. A recent paper by Neri and Heeger takes this type of methodology a step further, and succeeds in isolating and characterizing non-linear mechanisms responsible for the detection and identification of a specific visual target.

Original language	English (US)
Pages (from-to)	51-53
Number of pages	3
Journal	Trends in Cognitive Sciences
Volume	7
Issue number	2
DOIs	https://doi.org/10.1016/S1364-6613(02)00043-8
State	Published - Feb 1 2003

ASJC Scopus subject areas

Neuropsychology and Physiological Psychology
Experimental and Cognitive Psychology
Cognitive Neuroscience

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10.1016/S1364-6613(02)00043-8

Cite this

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abstract = "How do observers detect the presence of objects or features in visual images? Stochastic stimuli (for example, white noise) have become popular choices for providing a linear characterization of early sensory mechanisms. A recent paper by Neri and Heeger takes this type of methodology a step further, and succeeds in isolating and characterizing non-linear mechanisms responsible for the detection and identification of a specific visual target.",

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AB - How do observers detect the presence of objects or features in visual images? Stochastic stimuli (for example, white noise) have become popular choices for providing a linear characterization of early sensory mechanisms. A recent paper by Neri and Heeger takes this type of methodology a step further, and succeeds in isolating and characterizing non-linear mechanisms responsible for the detection and identification of a specific visual target.

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Seeing patterns in the noise

Abstract

ASJC Scopus subject areas

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