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Computational insights into human perceptual expertise for familiar and unfamiliar face recognition
Cognition 208 (C):104341 (2021)
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Citations of this work
Deep learning of shared perceptual representations for familiar and unfamiliar faces: Reply to commentaries.Nicholas M. Blauch, Marlene Behrmann & David C. Plaut - 2021 - Cognition 208 (C):104484.
From concepts to percepts in human and machine face recognition: A reply to Blauch, Behrmann & Plaut.Galit Yovel & Naphtali Abudarham - 2021 - Cognition 208 (C):104424.
Partitioning natural face image variability emphasises within-identity over between-identity representation for understanding accurate recognition.David White, Tanya Wayne & Victor P. L. Varela - 2022 - Cognition 219 (C):104966.
Seeing through disguise: Getting to know you with a deep convolutional neural network.Eilidh Noyes, Connor J. Parde, Y. Ivette Colón, Matthew Q. Hill, Carlos D. Castillo, Rob Jenkins & Alice J. O'Toole - 2021 - Cognition 211 (C):104611.
Insights from computational models of face recognition: A reply to Blauch, Behrmann and Plaut.Andrew W. Young & A. Mike Burton - 2021 - Cognition 208 (C):104422.
References found in this work
Critical features for face recognition.Naphtali Abudarham, Lior Shkiller & Galit Yovel - 2019 - Cognition 182 (C):73-83.
Robust social categorization emerges from learning the identities of very few faces.Robin S. S. Kramer, Andrew W. Young, Matthew G. Day & A. Mike Burton - 2017 - Psychological Review 124 (2):115-129.
Verification of face identities from images captured on video.Vicki Bruce, Zoë Henderson, Karen Greenwood, Peter J. B. Hancock, A. Mike Burton & Paul Miller - 1999 - Journal of Experimental Psychology: Applied 5 (4):339.
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