James D. Dunn

498 total citations
18 papers, 249 citations indexed

About

James D. Dunn is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, James D. Dunn has authored 18 papers receiving a total of 249 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cognitive Neuroscience, 12 papers in Computer Vision and Pattern Recognition and 4 papers in Social Psychology. Recurrent topics in James D. Dunn's work include Face Recognition and Perception (16 papers), Face recognition and analysis (8 papers) and Visual Attention and Saliency Detection (5 papers). James D. Dunn is often cited by papers focused on Face Recognition and Perception (16 papers), Face recognition and analysis (8 papers) and Visual Attention and Saliency Detection (5 papers). James D. Dunn collaborates with scholars based in Australia, United Kingdom and United States. James D. Dunn's co-authors include David White, Richard I. Kemp, Alice Towler, A. Mike Burton, Josh P. Davis, Sébastien Miellet, Kay L. Ritchie, Vicki Bruce, Davide Rivolta and Michele Masini and has published in prestigious journals such as PLoS ONE, Scientific Reports and Psychological Science.

In The Last Decade

James D. Dunn

16 papers receiving 244 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
James D. Dunn Australia	7	192	151	80	50	17	18	249
Jacqueline G. Cavazos United States	5	141 0.7×	167 1.1×	54 0.7×	34 0.7×	39 2.3×	6	260
Matthew C. Fysh United Kingdom	11	290 1.5×	207 1.4×	142 1.8×	68 1.4×	20 1.2×	24	358
Géraldine Jeckeln United States	4	129 0.7×	158 1.0×	49 0.6×	34 0.7×	40 2.4×	7	248
Christopher A. Longmore United Kingdom	8	241 1.3×	117 0.8×	150 1.9×	52 1.0×	6 0.4×	11	320
Samuel Weimer United States	4	101 0.5×	190 1.3×	43 0.5×	16 0.3×	102 6.0×	6	250
Genevieve L. Quek Australia	12	305 1.6×	61 0.4×	95 1.2×	45 0.9×	7 0.4×	28	346
Yetta Kwailing Wong Hong Kong	10	363 1.9×	60 0.4×	189 2.4×	42 0.8×	27 1.6×	27	405
Faye Skelton United Kingdom	10	237 1.2×	174 1.2×	61 0.8×	94 1.9×	26 1.5×	20	267
Hayley Ness United Kingdom	6	270 1.4×	231 1.5×	91 1.1×	87 1.7×	40 2.4×	14	318
Andrea Weidenfeld Germany	8	149 0.8×	49 0.3×	82 1.0×	15 0.3×	2 0.1×	11	303

Countries citing papers authored by James D. Dunn

Since Specialization

Citations

This map shows the geographic impact of James D. Dunn's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by James D. Dunn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James D. Dunn more than expected).

Fields of papers citing papers by James D. Dunn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James D. Dunn. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by James D. Dunn. The network helps show where James D. Dunn may publish in the future.

Co-authorship network of co-authors of James D. Dunn

This figure shows the co-authorship network connecting the top 25 collaborators of James D. Dunn. A scholar is included among the top collaborators of James D. Dunn based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James D. Dunn. James D. Dunn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Dunn, James D., et al.. (2025). Super-recognizers sample visual information of superior computational value for facial recognition. Proceedings of the Royal Society B Biological Sciences. 292(2058). 20252005–20252005.

Dunn, James D., Sébastien Miellet, & David White. (2024). Information sampling differences supporting superior face identity processing ability. Psychonomic Bulletin & Review. 32(2). 801–811. 1 indexed citations

Dunn, James D., et al.. (2024). Flexible use of facial features supports face identity processing.. Journal of Experimental Psychology Human Perception & Performance. 50(12). 1143–1153. 1 indexed citations

Dunn, James D., Alice Towler, Richard I. Kemp, & David White. (2023). Selecting police super-recognisers. PLoS ONE. 18(5). e0283682–e0283682. 5 indexed citations

Passarelli, Marcello, James D. Dunn, Michele Masini, et al.. (2023). Self-reported face recognition abilities moderately predict face-learning skills: Evidence from Italian samples. Heliyon. 9(3). e14125–e14125. 6 indexed citations

Miellet, Sébastien, et al.. (2023). The computational value of face information sampled by super-recognizers. Journal of Vision. 23(9). 4744–4744.

Towler, Alice, et al.. (2023). Diverse types of expertise in facial recognition. Scientific Reports. 13(1). 10 indexed citations

Dunn, James D., et al.. (2022). Face-Information Sampling in Super-Recognizers. Psychological Science. 33(9). 1615–1630. 20 indexed citations

Growns, Bethany, James D. Dunn, Rebecca K. Helm, Alice Towler, & Jeff Kukucka. (2022). The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices. PLoS ONE. 17(8). e0272338–e0272338. 3 indexed citations

10.

Growns, Bethany, Alice Towler, James D. Dunn, et al.. (2022). Statistical feature training improves fingerprint-matching accuracy in novices and professional fingerprint examiners. Cognitive Research Principles and Implications. 7(1). 60–60. 4 indexed citations

11.

Dunn, James D., et al.. (2022). Verifying unfamiliar identities: Effects of processing name and face information in the same identity-matching task. Cognitive Research Principles and Implications. 7(1). 92–92. 2 indexed citations

12.

Dunn, James D., Richard I. Kemp, & David White. (2021). Top-down influences on working memory representations of faces: Evidence from dual-target visual search. Quarterly Journal of Experimental Psychology. 74(8). 1368–1377. 4 indexed citations

13.

Dunn, James D., et al.. (2020). UNSW Face Test: A screening tool for super-recognizers. PLoS ONE. 15(11). e0241747–e0241747. 30 indexed citations

14.

Towler, Alice, Richard I. Kemp, Vicki Bruce, et al.. (2019). Are face recognition abilities in humans and sheep really ‘comparable’?. Royal Society Open Science. 6(1). 180772–180772. 5 indexed citations

15.

Towler, Alice, et al.. (2019). Do professional facial image comparison training courses work?. PLoS ONE. 14(2). e0211037–e0211037. 57 indexed citations

16.

Dunn, James D., Kay L. Ritchie, Richard I. Kemp, & David White. (2019). Familiarity does not inhibit image-specific encoding of faces.. Journal of Experimental Psychology Human Perception & Performance. 45(7). 841–854. 8 indexed citations

17.

Dunn, James D., Richard I. Kemp, & David White. (2018). Search templates that incorporate within-face variation improve visual search for faces. Cognitive Research Principles and Implications. 3(1). 10 indexed citations

18.

White, David, et al.. (2015). Error Rates in Users of Automatic Face Recognition Software. PLoS ONE. 10(10). e0139827–e0139827. 83 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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