Data-driven studies in face identity processing rely on the quality of the tests and data sets

[1]  Meike Ramon,et al.  Improving forensic perpetrator identification with Super-Recognizers , 2023, Proceedings of the National Academy of Sciences of the United States of America.

[2]  C. Mondloch,et al.  Stable individual differences in unfamiliar face identification: Evidence from simultaneous and sequential matching tasks , 2022, Cognition.

[3]  Daniel J. Carragher,et al.  Simulated automated facial recognition systems as decision-aids in forensic face matching tasks. , 2022, Journal of experimental psychology. General.

[4]  A. Young,et al.  Understanding trait impressions from faces , 2022, British journal of psychology.

[5]  M. Banissy,et al.  Face specific inversion effects provide evidence for two subtypes of developmental prosopagnosia , 2022, Neuropsychologia.

[6]  Meike Ramon,et al.  Face Recognition in Police Officers:Who Fits the Bill? , 2022, Forensic Science International: Reports.

[7]  Meike Ramon,et al.  Accurate but inefficient: Standard face identity matching tests fail to identify prosopagnosia , 2021, Neuropsychologia.

[8]  J. DeGutis,et al.  Distinct abilities associated with matching same identity faces versus discriminating different faces: Evidence from individual differences in prosopagnosics and controls , 2021, Quarterly journal of experimental psychology.

[9]  Matthew V. Pachai,et al.  Psychophysical profiles in super-recognizers , 2021, Scientific Reports.

[10]  E. Portch,et al.  When two fields collide: Identifying “super-recognisers” for neuropsychological and forensic face recognition research , 2021, Quarterly journal of experimental psychology.

[11]  A. Jones,et al.  Facial first impressions form two clusters representing approach-avoidance , 2021, Cognitive Psychology.

[12]  David White,et al.  GFMT2: A psychometric measure of face matching ability , 2021, Behavior Research Methods.

[13]  B. Duchaine,et al.  The Oxford Face Matching Test: A non-biased test of the full range of individual differences in face perception , 2021, Behavior Research Methods.

[14]  Meike Ramon.  Super-Recognizers – a novel diagnostic framework, 70 cases, and guidelines for future work , 2021, Neuropsychologia.

[15]  D. Barr,et al.  Understanding Mixed-Effects Models Through Data Simulation , 2021 .

[16]  A. Jones,et al.  Individual differences in face and voice matching abilities: The relationship between accuracy and consistency , 2020, Applied Cognitive Psychology.

[17]  Meike Ramon,et al.  Differences between and within individuals, and subprocesses of face cognition: implications for theory, research and personnel selection , 2020, Royal Society Open Science.

[18]  Josh P. Davis,et al.  UNSW Face Test: A screening tool for super-recognizers , 2020, PloS one.

[19]  John T Wixted,et al.  Science is not a signal detection problem , 2020, Proceedings of the National Academy of Sciences.

[20]  R. Caldara,et al.  Normative data for two challenging tests of face matching under ecological conditions , 2020, Cognitive Research: Principles and Implications.

[21]  T. Yarkoni,et al.  The generalizability crisis , 2019, Behavioral and Brain Sciences.

[22]  David Liljequist,et al.  Intraclass correlation – A discussion and demonstration of basic features , 2019, PloS one.

[23]  Katie L. H. Gray,et al.  Is developmental prosopagnosia best characterised as an apperceptive or mnemonic condition? , 2019, Neuropsychologia.

[24]  Mario J. Baldassari,et al.  The importance of decision bias for predicting eyewitness lineup choices: toward a Lineup Skills Test , 2018, Cognitive Research.

[25]  P. Hancock,et al.  A grey area: how does image hue affect unfamiliar face matching? , 2018, Cognitive Research.

[26]  Josh P. Davis,et al.  Cognitive and neural markers of super-recognisers’ face processing superiority and enhanced cross-age effect , 2018, Cortex.

[27]  W. Sommer,et al.  All Categories Are Equal, but Some Categories Are More Equal Than Others: The Psychometric Structure of Object and Face Cognition , 2018, Journal of experimental psychology. Learning, memory, and cognition.

[28]  Matthew Q. Hill,et al.  Face recognition ability does not predict person identification performance: using individual data in the interpretation of group results , 2018, Cognitive research: principles and implications.

[29]  David J. Robertson,et al.  Individual differences in face identity processing , 2018, Cognitive Research: Principles and Implications.

[30]  D. White,et al.  Improving face identification with specialist teams , 2018, Cognitive research: principles and implications.

[31]  Sarah Bate,et al.  Applied screening tests for the detection of superior face recognition , 2018, Cognitive Research: Principles and Implications.

[32]  Matthew Q. Hill,et al.  Face recognition ability does not predict person identification performance: using individual data in the interpretation of group results , 2018, Cognitive Research: Principles and Implications.

[33]  Swami Sankaranarayanan,et al.  Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms , 2018, Proceedings of the National Academy of Sciences.

[34]  Matthew C Fysh,et al.  The Kent Face Matching Test , 2018, British journal of psychology.

[35]  Markus Bindemann,et al.  Cross-race correlations in the abilities to match unfamiliar faces. , 2018, Acta psychologica.

[36]  M. Gobbini,et al.  Familiarity matters: A review on prioritized processing of personally familiar faces , 2018 .

[37]  Meike Ramon.  The power of how—lessons learned from neuropsychology and face processing , 2018, Cognitive neuropsychology.

[38]  Sarah Bate,et al.  Super-recognition in development: A case study of an adolescent with extraordinary face recognition skills , 2017, Cognitive neuropsychology.

[39]  John T Wixted,et al.  The Relationship Between Eyewitness Confidence and Identification Accuracy: A New Synthesis , 2017, Psychological science in the public interest : a journal of the American Psychological Society.

[40]  A. Burton,et al.  Face Matching Impairment in Developmental Prosopagnosia , 2017, Quarterly journal of experimental psychology.

[41]  Jenny M. Bosten,et al.  General and specific factors in the processing of faces , 2017, Vision Research.

[42]  Gilles E. Gignac,et al.  Effect size guidelines for individual differences researchers , 2016 .

[43]  Josh P. Davis,et al.  Investigating predictors of superior face recognition ability in police super-recognisers , 2016 .

[44]  Anna K. Bobak,et al.  Detecting Superior Face Recognition Skills in a Large Sample of Young British Adults , 2016, Front. Psychol..

[45]  Sarah Bate,et al.  An in-depth cognitive examination of individuals with superior face recognition skills , 2016, Cortex.

[46]  Terry K Koo,et al.  A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. , 2016, Journal Chiropractic Medicine.

[47]  Rob Jenkins,et al.  Face Recognition by Metropolitan Police Super-Recognisers , 2016, PloS one.

[48]  Sarah Bate,et al.  Solving the Border Control Problem: Evidence of Enhanced Face Matching in Individuals with Extraordinary Face Recognition Skills , 2016, PloS one.

[49]  Peter J. B. Hancock,et al.  Super‐recognisers in Action: Evidence from Face‐matching and Face Memory Tasks , 2015, Applied cognitive psychology.

[50]  Matthew Q. Hill,et al.  Perceptual expertise in forensic facial image comparison , 2015, Proceedings of the Royal Society B: Biological Sciences.

[51]  Justin Duncan,et al.  When less is more: Impact of face processing ability on recognition of visually degraded faces. , 2015, Journal of experimental psychology. Human perception and performance.

[52]  Isabel Gauthier,et al.  The Vanderbilt holistic face processing test: a short and reliable measure of holistic face processing. , 2014, Journal of vision.

[53]  A. Young,et al.  Modeling first impressions from highly variable facial images , 2014, Proceedings of the National Academy of Sciences.

[54]  Laura Germine,et al.  Face recognition ability matures late: evidence from individual differences in young adults. , 2013, Journal of experimental psychology. Human perception and performance.

[55]  Adam W. McCrimmon,et al.  Review of the Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II) , 2013 .

[56]  Stephen Bailey,et al.  Principal Component Analysis with Noisy and/or Missing Data , 2012, 1208.4122.

[57]  Kim F. Nimon,et al.  The Assumption of a Reliable Instrument and Other Pitfalls to Avoid When Considering the Reliability of Data , 2012, Front. Psychology.

[58]  A. Burton,et al.  Variability in photos of the same face , 2011, Cognition.

[59]  W. Sommer,et al.  On the specificity of face cognition compared with general cognitive functioning across adult age. , 2011, Psychology and aging.

[60]  M. Tavakol,et al.  Making sense of Cronbach's alpha , 2011, International journal of medical education.

[61]  Bruce A. Draper,et al.  An introduction to the good, the bad, & the ugly face recognition challenge problem , 2011, Face and Gesture 2011.

[62]  A. Burton,et al.  The Glasgow Face Matching Test , 2010, Behavior research methods.

[63]  G. Yovel,et al.  Diagnosing prosopagnosia: Effects of ageing, sex, and participant–stimulus ethnic match on the Cambridge Face Memory Test and Cambridge Face Perception Test , 2009, Cognitive neuropsychology.

[64]  K. Nakayama,et al.  Super-recognizers: People with extraordinary face recognition ability , 2009, Psychonomic bulletin & review.

[65]  Ahmed M. Megreya,et al.  Hits and false positives in face matching: A familiarity-based dissociation , 2007, Perception & psychophysics.

[66]  Alice J. O'Toole,et al.  Face Recognition Algorithms Surpass Humans Matching Faces Over Changes in Illumination , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[67]  K. Nakayama,et al.  Please Scroll down for Article Cognitive Neuropsychology Family Resemblance: Ten Family Members with Prosopagnosia and Within-class Object Agnosia , 2022 .

[68]  D. Cook,et al.  Current concepts in validity and reliability for psychometric instruments: theory and application. , 2006, The American journal of medicine.

[69]  Nigel O'Brian,et al.  Generalizability Theory I , 2003 .

[70]  P. Barata,et al.  When Two Fields Collide , 2003 .

[71]  Paul Miller,et al.  Verification of face identities from images captured on video. , 1999 .

[72]  D. Altman,et al.  Statistics notes: Cronbach's alpha , 1997 .

[73]  Simon Nuttall.  The Grey Area , 1992 .

[74]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[75]  J. H. Ward.  Hierarchical Grouping to Optimize an Objective Function , 1963 .

[76]  Rob Jenkins,et al.  Identity From Variation: Representations of Faces Derived From Multiple Instances , 2016, Cogn. Sci..

[77]  Michael G. Strintzis,et al.  Face Recognition , 2006, Encyclopedia of Multimedia.

[78]  V. Bruce,et al.  Face processing: Human perception and principal components analysis , 1996, Memory & cognition.

[79]  Meike Ramon,et al.  Image or identity? Only Super-Recognizers’ 
(memor)ability is consistently viewpoint-invariant , 2022 .