ORCID as entered in ROS

Select Publications
2021, Diverse routes to expertise in facial recognition, http://dx.doi.org/10.31234/osf.io/fmznh
,2021, Face information sampling in super-recognizers, http://dx.doi.org/10.31234/osf.io/z2k4a
,2021, GFMT2: A psychometric measure of face matching ability, http://dx.doi.org/10.31234/osf.io/a3fh4
,2021, Masked face identification is improved by diagnostic feature training, http://dx.doi.org/10.31234/osf.io/e9fq3
,2021, Partitioning natural face image variability emphasises within-identity over between-identity representation for understanding accurate recognition, http://dx.doi.org/10.31234/osf.io/w58k3
,2020, Performance of Typical and Superior Face Recognisers on a Novel Interactive Face Matching Procedure, http://dx.doi.org/10.31234/osf.io/kbm2g
,2020, Can face identification ability be trained? Evidence for two routes to expertise, http://dx.doi.org/10.31234/osf.io/g7qfd
,2020, Understanding professional expertise in unfamiliar face matching, http://dx.doi.org/10.31234/osf.io/z2ugp
,2020, UNSW Face Test: A screening tool for super-recognizers, http://dx.doi.org/10.31234/osf.io/k7mf6
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