Mayu Nishimura

1.1k citations
30 papers · 721 · h-index 16

Impact in

Papers in

    • Face Recognition and Perception 20
    • Visual perception and processing mechanisms 14
    • Neural and Behavioral Psychology Studies 4
    • Aesthetic Perception and Analysis 3
    • Autism Spectrum Disorder Research 2
    • Evolutionary Psychology and Human Behavior 8

Mayu Nishimura

29 papers receiving 709 citations

Peers

Mayu Nishimura
Comparison fields: 5 of 74
  • Cognitive Neuroscience 576
  • Experimental and Cognitive Psychology 238
  • Computer Vision and Pattern Recognition 151
  • Behavioral Neuroscience 23
  • Developmental and Educational Psychology 78
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Citations per field
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Citations per year

Countries citing papers authored by Mayu Nishimura

Since Specialization
Citations

This map shows the geographic impact of Mayu Nishimura'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 Mayu Nishimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayu Nishimura more than expected).

Fields of papers citing papers by Mayu Nishimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mayu Nishimura. 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 Mayu Nishimura. The network helps show where Mayu Nishimura may publish in the future.

Co-authors

The 25 scholars most cited alongside Mayu Nishimura, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mayu Nishimura Line = papers co-authored together Mayu Nishimura links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
What are you looking at? Acuity for triadic eye gaze.
200499
2 201185
3 201758
4 201050
5 200848
6 200939
7 201038
8 200938
9 200836
10 200934
11 201426
12 201823
13 200321
14 200820
15 201620
16 201917
17 201114
18 201010
19 201310
20 20209

About Mayu Nishimura

Mayu Nishimura is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition, Epidemiology and Ophthalmology, having authored 30 papers that have together received 721 indexed citations. Recurring topics across this work include Face Recognition and Perception (20 papers), Visual perception and processing mechanisms (14 papers), Evolutionary Psychology and Human Behavior (8 papers), Ophthalmology and Visual Impairment Studies (4 papers), Neural and Behavioral Psychology Studies (4 papers), Visual Attention and Saliency Detection (3 papers), Aesthetic Perception and Analysis (3 papers) and Autism Spectrum Disorder Research (2 papers). The work is most often cited by research in Cognitive Neuroscience (576 citations), Experimental and Cognitive Psychology (238 citations), Computer Vision and Pattern Recognition (151 citations), Behavioral Neuroscience (23 citations) and Developmental and Educational Psychology (78 citations). Mayu Nishimura has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Daphne Maurer, Marlene Behrmann, Kang Lee, Xiaoqing Gao, Lawrence A. Symons, Sabine Kästner, Christina S. Konen, K. Suzanne Scherf, Gillian Rhodes and Linda Jeffery. Their work appears in journals such as Developmental Science, Journal of Vision, Neuropsychologia, Journal of Experimental Child Psychology and Perception.

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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