98%
921
2 minutes
20
Individuals are better at recognizing faces from their own ethnic group compared with other ethnicity faces-the (OEE). This finding is said to reflect differences in experience and familiarity to faces from other ethnicities relative to faces corresponding with the viewers' ethnicity. However, own-ethnicity face recognition performance ranges considerably within a population, from very poor to extremely good. In addition, within-population recognition performance on other-ethnicity faces can also vary considerably with some individuals being classed as " (Wan et al., 2017). Despite evidence for considerable variation in performance within population for faces of both types, it is currently unclear whether the magnitude of the OEE changes as a function of this variability. By recruiting large-scale multinational samples, we investigated the size of the OEE across the full range of own and other ethnicity face performance while considering measures of social contact. We find that the magnitude of the OEE is remarkably consistent across all levels of within-population own- and other-ethnicity face recognition ability, and this pattern was unaffected by social contact measures. These findings suggest that the OEE is a persistent feature of face recognition performance, with consequences for models built around very poor, and very good face recognizers. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1037/xhp0000762 | DOI Listing |
Psychon Bull Rev
September 2025
Department of Experimental Psychology, University of Oxford, Oxford, UK.
Individuals who are superior at face recognition are described as 'super recognisers' (SRs). On standard face recognition tasks SRs outperform individuals who have typical face recognition ability. However, high accuracy on face recognition tasks may be driven by superior ability in one or more of several component processes including face perception, face matching, and face memory.
View Article and Find Full Text PDFAnal Bioanal Chem
September 2025
School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou, 310018, China.
The prompt and accurate identification of pathogenic bacteria is crucial for mitigating the transmission of infections. Conventional detection methods face limitations, including lengthy processing, complex sample pretreatment, high instrumentation costs, and insufficient sensitivity for rapid on-site screening. To address these challenges, an aptamer (Apt)-sensor based on functionalized magnetic nanoparticles (MNPs) was developed for detecting Escherichia coli.
View Article and Find Full Text PDFNeural Netw
September 2025
School of Cyberspace Security (School of Cryptology), Hainan University, No. 58, Renmin Avenue, Haikou, 570228, Hainan, China. Electronic address:
The primary challenge of large-margin learning lies in designing classifiers with strong discriminative power. Although existing large margin methods have achieved success in various classification tasks, they often suffer from weak task generalization and imbalanced handling of easy and hard samples. In this paper, we propose a margin adaptive synthetic virtual Softmax loss (SV-Softmax), which dynamically generates virtual prototypes by synthesizing embedded features and their corresponding prototypes.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Psychology & Sociology, Texas A&M University - Corpus Christi, Corpus Christi, Texas, United States of America.
While the use of personal protective equipment protects healthcare workers against transmissible disease, it also obscures the lower facial regions that are vital for transmitting emotion signals. Previous studies have found that face coverings can impair recognition of emotional expressions, particularly those that rely on signals from the lower regions of the face, such as disgust. Recent research on the individual differences that may influence expression recognition, such as emotional intelligence, has shown mixed results.
View Article and Find Full Text PDFJ Vis
September 2025
Neuroscience Program, Western University, London, ON, Canada.
Studies of visual face processing often use flat images as proxies for real faces due to their ease of manipulation and experimental control. Although flat images capture many features of a face, they lack the rich three-dimensional (3D) structural information available when binocularly viewing real faces (e.g.
View Article and Find Full Text PDF