Eilidh Noyes

1.2k total citations
15 papers, 648 citations indexed

About

Eilidh Noyes is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Eilidh Noyes has authored 15 papers receiving a total of 648 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 12 papers in Cognitive Neuroscience and 9 papers in Experimental and Cognitive Psychology. Recurrent topics in Eilidh Noyes's work include Face recognition and analysis (13 papers), Face Recognition and Perception (12 papers) and Evolutionary Psychology and Human Behavior (8 papers). Eilidh Noyes is often cited by papers focused on Face recognition and analysis (13 papers), Face Recognition and Perception (12 papers) and Evolutionary Psychology and Human Behavior (8 papers). Eilidh Noyes collaborates with scholars based in United Kingdom, United States and Australia. Eilidh Noyes's co-authors include Rob Jenkins, Alice J. O’Toole, Kay L. Ritchie, A. Mike Burton, Katie L. H. Gray, Josh P. Davis, Jacqueline G. Cavazos, David J. Robertson, Carina A. Hahn and Géraldine Jeckeln and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Cognition.

In The Last Decade

Eilidh Noyes

14 papers receiving 626 citations

Peers

Countries citing papers authored by Eilidh Noyes

Since Specialization

Citations

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

Fields of papers citing papers by Eilidh Noyes

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eilidh Noyes

This figure shows the co-authorship network connecting the top 25 collaborators of Eilidh Noyes. A scholar is included among the top collaborators of Eilidh Noyes 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 Eilidh Noyes. Eilidh Noyes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Training human super-recognizers’ detection and discrimination of AI-generated faces 2025 ·Royal Society Open Science ·Katie L. H. Gray, Josh P. Davis, (unknown), Eilidh Noyes, Kay L. Ritchie	0
2	The effect of facial ageing on forensic facial image comparison 2024 ·Applied Cognitive Psychology ·(unknown), (unknown), Eilidh Noyes, (unknown), (unknown)	1
3	Face masks and fake masks: the effect of real and superimposed masks on face matching with super-recognisers, typical observers, and algorithms 2024 ·Cognitive Research Principles and Implications ·Kay L. Ritchie, Daniel J. Carragher, Josh P. Davis, (unknown), (unknown), Eilidh Noyes, Katie L. H. Gray, Peter Hancock	4
4	The effect of face masks and sunglasses on identity and expression recognition with super-recognizers and typical observers 2021 ·Royal Society Open Science ·Eilidh Noyes, Josh P. Davis, (unknown), Katie L. H. Gray, Kay L. Ritchie	124
5	Seeing through disguise: Getting to know you with a deep convolutional neural network 2021 ·Cognition ·Eilidh Noyes, Connor J. Parde, (unknown), Matthew Q. Hill, Carlos D. Castillo, Rob Jenkins, Alice J. O’Toole	10
6	Deliberate disguise in face identification. 2019 ·Journal of Experimental Psychology Applied ·Eilidh Noyes, Rob Jenkins	32
7	Face recognition ability does not predict person identification performance: using individual data in the interpretation of group results 2018 ·Cognitive Research Principles and Implications ·Eilidh Noyes, Matthew Q. Hill, Alice J. O’Toole	19
8	Enhancing CCTV: Averages improve face identification from poor‐quality images 2018 ·Applied Cognitive Psychology ·Kay L. Ritchie, David White, Robin S. S. Kramer, Eilidh Noyes, Rob Jenkins, A. Mike Burton	16
9	Learning context and the other-race effect: Strategies for improving face recognition 2018 ·Vision Research ·Jacqueline G. Cavazos, Eilidh Noyes, Alice J. O’Toole	14
10	Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms 2018 ·Proceedings of the National Academy of Sciences ·P. Jonathon Phillips, Amy N. Yates, Ying Hu, Carina A. Hahn, Eilidh Noyes, (unknown), Jacqueline G. Cavazos, Géraldine Jeckeln, Rajeev Ranjan, Swami Sankaranarayanan, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa, David White, Alice J. O’Toole	216
11	Wisdom of the social versus non‐social crowd in face identification 2018 ·British Journal of Psychology ·Géraldine Jeckeln, Carina A. Hahn, Eilidh Noyes, Jacqueline G. Cavazos, Alice J. O’Toole	18
12	Hyper-realistic face masks: a new challenge in person identification 2017 ·Cognitive Research Principles and Implications ·(unknown), Yoshiyuki Ueda, (unknown), Eilidh Noyes, Sakiko Yoshikawa, Rob Jenkins	22
13	Camera-to-subject distance affects face configuration and perceived identity 2017 ·Cognition ·Eilidh Noyes, Rob Jenkins	41
14	What is a super-recogniser? 2017 ·Huddersfield Research Portal (University of Huddersfield) ·Eilidh Noyes, Peter J. Phillips, Alice J. O’Toole	18
15	Face Recognition by Metropolitan Police Super-Recognisers 2016 ·PLoS ONE ·David J. Robertson, Eilidh Noyes, (unknown), Rob Jenkins, A. Mike Burton	113

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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