Computational insights into human perceptual expertise for familiar and unfamiliar face recognition

doi:10.1016/j.cognition.2020.104341

Paper

Computational insights into human perceptual expertise for familiar and unfamiliar face recognition

Published Oct 24, 2019 · Nicholas M. Blauch, M. Behrmann, D. Plaut

Cognition

Q1 SJR score

48

Citations

3

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Abstract

Abstract removed due to Elsevier request; this does not indicate any issues with the research. Click the full text link above to read the abstract and view the original source.

Very Rigorous Journal

Study Snapshot

Key takeawayFace training improves identity verification for unfamiliar faces, highlighting the generalization of identity-invariant information in face images.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

Computational insights into human perceptual expertise for familiar and unfamiliar face recognition

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