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Face Recognition and Perception

Face Recognition and Perception is a research topic within Cognitive Neuroscience. Science Explorer counts 18k research works in it since 1950. 19.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the neural mechanisms underlying face perception, recognition, and emotional expression processing in the human brain. It delves into topics such as the distributed cortical network for face perception, functional compartmentalization in the ventral temporal cortex, and the role of social cognition in facial identity and emotion recognition. The use of fMRI data and multivariate pattern analysis is prominent in decoding mental states and visual contents from brain activity.

  • Face Perception
  • Neural Mechanisms
  • Visual Cortex
  • Emotional Expressions
  • fMRI Data
  • Social Cognition
  • Object Recognition
  • Facial Identity
  • Cortical Processing
  • Emotion Recognition
Research works
18k
fractional, since 1950
In the world top 10%
3.7k
per year above
Top-10% rate
19.9%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+0%
the tick is no change

Which countries lead Face Recognition and Perception research?

By volume, the United States and China publish the most (729 and 381 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 729 works
  2. 2 China 381 works
  3. 3 United Kingdom 278 works
  4. 4 Germany 239 works
  5. 5 Japan 197 works
  6. 6 Canada 159 works
  7. 7 Italy 132 works
  8. 8 France 108 works
  9. 9 Australia 96 works
  10. 10 Netherlands 75 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 30.5%China: 15.9%United Kingdom: 11.6%Germany: 10.0%6 others listed: 32.0%30%largest
United States729 · 30.5%China381 · 15.9%United Kingdom278 · 11.6%Germany239 · 10.0%6 others listed766 · 32.0%

Shares of the rows listed above, not of the whole node.

Which institutions lead Face Recognition and Perception research?

By volume in 2022–2025, The University of Queensland publishes the most Face Recognition and Perception research, followed by University of York and Johns Hopkins University.

By volume, 2022–2025

  1. 1 The University of Queensland Australia 20 works
  2. 2 University of York United Kingdom 19 works
  3. 3 Johns Hopkins University United States 18 works
  4. 4 Harvard University United States 18 works
  5. 5 University College London United Kingdom 18 works
  6. 6 University of Toronto Canada 18 works
  7. 7 KU Leuven Belgium 17 works
  8. 8 Centre National de la Recherche Scientifique France 16 works
  9. 9 Justus-Liebig-Universität Gießen Germany 15 works
  10. 10 Tel Aviv University Israel 14 works

Who are the leading researchers in Face Recognition and Perception?

The most-cited researchers publishing on Face Recognition and Perception include James A. Russell, Simon Baron‐Cohen and L. Gauthier.

  1. 1 James A. Russell 5k citations
  2. 2 Simon Baron‐Cohen 3.8k citations
  3. 3 L. Gauthier 3.7k citations
  4. 4 John T. Cacioppo 3.7k citations
  5. 5 Huchuan Lu 3.2k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Face Recognition and Perception research done?

The largest centres of Face Recognition and Perception research in 2022–2025 are Beijing (China), Tokyo (Japan), London (United Kingdom) and New York (United States).

Largest cities, 2022–2025

  1. 1 Beijing China 87 works
  2. 2 Tokyo Japan 67 works
  3. 3 London United Kingdom 60 works
  4. 4 New York United States 41 works
  5. 5 Paris France 40 works
  6. 6 Toronto Canada 39 works
  7. 7 Cambridge United States 32 works
  8. 8 Shanghai China 31 works
  9. 9 Guangzhou China 30 works
  10. 10 Berlin Germany 30 works
See Face Recognition and Perception on the map

Where is the best place to study Face Recognition and Perception?

Among universities, judged by research, University of York, Radboud University Nijmegen and Justus-Liebig-Universität Gießen score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%10%20%30%mean 20.04%fractional works in this node (log) →share in the world top 10% →University of York: 19, 11.5%Radboud University Nijmegen: 13, 24.6%Justus-Liebig-Universität Gießen: 14, 23.0%The University of Queensland: 20, 18.1%Bournemouth University: 10, 15.8%University of Milano-Bicocca: 11, 22.2%University of Lincoln: 10, 16.0%Johns Hopkins University: 18, 25.0%University of Trento: 9, 20.6%Dartmouth College: 10, 23.6%Radboud University N…Justus-Liebig-Univer…The University of Qu…University of York
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1University of York United Kingdom 68.411.5%21.9×19 +120.6%
2Radboud University Nijmegen Netherlands 67.924.6%10.6×13 -4.5%
3Justus-Liebig-Universität Gießen Germany 67.423.0%22.8×14 +44.3%
4The University of Queensland Australia 63.218.1%8.3×20 -32.3%
5Bournemouth University United Kingdom 62.515.8%35.5×10 +311.5%
6University of Milano-Bicocca Italy 60.522.2%13.2×11 +29.6%
7University of Lincoln United Kingdom 59.816.0%33.6×10 +139.4%
8Johns Hopkins University United States 58.225.0%5.9×18 -18.5%
9University of Trento Italy 54.920.6%11.5×9 +27.2%
10Dartmouth College United States 54.223.6%17.4×10 -41.8%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Face Recognition and Perception research growing?

Output in 2018–2022 was 0% higher than in 2013–2017, peaking in 2010. The fastest-growing topics are Face Recognition and Perception.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.