scholarly journals Enhanced Matching of Children’s Faces in “Super-Recognisers” But Not High-Contact Controls

i-Perception ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 204166952094442
Author(s):  
Sarah Bate ◽  
Rachel Bennetts ◽  
Ebony Murray ◽  
Emma Portch
Keyword(s):  
Face Recognition ◽  
Young Children ◽  
Real World ◽  
Matching Task ◽  
Control Groups ◽  
Age Bias ◽  
Face Matching ◽  
Contact Control ◽  
Additional Exposure

Face matching is notoriously error-prone, and some work suggests additional difficulty when matching the faces of children. It is possible that individuals with natural proficiencies in adult face matching (“super-recognisers” [SRs]) will also excel at the matching of children’s faces, although other work implicates facilitations in typical perceivers who have high levels of contact with young children (e.g., nursery teachers). This study compared the performance of both of these groups on adult and child face matching to a group of low-contact controls. High- and low-contact control groups performed at a remarkably similar level in both tasks, whereas facilitations for adult and child face matching were observed in some (but not all) SRs. As a group, the SRs performed better in the adult compared with the child task, demonstrating an extended own-age bias compared with controls. These findings suggest that additional exposure to children’s faces does not assist the performance in a face matching task, and the mechanisms underpinning superior recognition of adult faces can also facilitate the child face recognition. Real-world security organisations should therefore seek individuals with general facilitations in face matching for both adult and child face matching tasks.

scholarly journals Tactile cortical responses and association with tactile reactivity in young children on the autism spectrum

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Svenja Espenhahn ◽  
Kate J. Godfrey ◽  
Sakshi Kaur ◽  
Maia Ross ◽  
Niloy Nath ◽  
...  
Keyword(s):  
Early Childhood ◽  
Young Children ◽  
Evoked Potentials ◽  
Real World ◽  
Somatosensory Evoked Potentials ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Childhood Autism ◽  
Verbal Abilities ◽  
Early Childhood Autism

Abstract Background Unusual behavioral reactions to sensory stimuli are frequently reported in individuals on the autism spectrum (AS). Despite the early emergence of sensory features (< age 3) and their potential impact on development and quality of life, little is known about the neural mechanisms underlying sensory reactivity in early childhood autism. Methods Here, we used electroencephalography (EEG) to investigate tactile cortical processing in young children aged 3–6 years with autism and in neurotypical (NT) children. Scalp EEG was recorded from 33 children with autism, including those with low cognitive and/or verbal abilities, and 45 age- and sex-matched NT children during passive tactile fingertip stimulation. We compared properties of early and later somatosensory-evoked potentials (SEPs) and their adaptation with repetitive stimulation between autistic and NT children and assessed whether these neural measures are linked to “real-world” parent-reported tactile reactivity. Results As expected, we found elevated tactile reactivity in children on the autism spectrum. Our findings indicated no differences in amplitude or latency of early and mid-latency somatosensory-evoked potentials (P50, N80, P100), nor adaptation between autistic and NT children. However, latency of later processing of tactile information (N140) was shorter in young children with autism compared to NT children, suggesting faster processing speed in young autistic children. Further, correlational analyses and exploratory analyses using tactile reactivity as a grouping variable found that enhanced early neural responses were associated with greater tactile reactivity in autism. Limitations The relatively small sample size and the inclusion of a broad range of autistic children (e.g., with low cognitive and/or verbal abilities) may have limited our power to detect subtle group differences and associations. Hence, replications are needed to verify these results. Conclusions Our findings suggest that electrophysiological somatosensory cortex processing measures may be indices of “real-world” tactile reactivity in early childhood autism. Together, these findings advance our understanding of the neurophysiological mechanisms underlying tactile reactivity in early childhood autism and, in the clinical context, may have therapeutic implications.

scholarly journals EEG recording during an emotional face-matching task in children of mothers with interpersonal violence-related posttraumatic stress disorder

2019 ◽  
Vol 283 ◽  
pp. 34-44
Author(s):  
Virginie C. Perizzolo ◽  
Cristina Berchio ◽  
Dominik A. Moser ◽  
Cristina Puro Gomez ◽  
Marylène Vital ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Interpersonal Violence ◽  
Stress Disorder ◽  
Matching Task ◽  
Face Matching ◽  
Emotional Face

scholarly journals Disease Network Delineates the Disease Progression Profile of Cardiovascular Diseases

2020 ◽  
Author(s):  
Zefang Tang ◽  
Yiqin Yu ◽  
Kenney Ng ◽  
Daby Sow ◽  
Jianying Hu ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Disease Progression ◽  
Real World ◽  
Disease Risk ◽  
Disease Network ◽  
Real World Data ◽  
Risk Models ◽  
Age Bias ◽  
Real World Evidence ◽  
Tremendous Amount

AbstractAs Electronic Health Records (EHR) data accumulated explosively in recent years, the tremendous amount of patient clinical data provided opportunities to discover real world evidence. In this study, a graphical disease network, named progressive cardiovascular disease network (progCDN), was built based on EHR data from 14.3 million patients 1 to delineate the progression profiles of cardiovascular diseases (CVD). The network depicted the dominant diseases in CVD development, such as the heart failure and coronary arteriosclerosis. Novel progression relationships were also discovered, such as the progression path from long QT syndrome to major depression. In addition, three age-group progCDNs identified a series of age-associated disease progression paths and important successor diseases with age bias. Furthermore, we extracted a list of salient features to build a series of disease risk models based on the progression pairs in the disease network. The progCDN network can be further used to validate or explore novel disease relationships in real world data. Features with sufficient abundance and high correlation can be widely applied to train disease risk models when using EHR data.

scholarly journals Real World of Artificial Intelligence - A Review

2020 ◽  
Vol 11 (2) ◽  
pp. 41-47
Author(s):  
Amandeep Kaur ◽  
Madhu Dhiman ◽  
Mansi Tonk ◽  
Ramneet Kaur
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Natural Language Processing ◽  
Face Recognition ◽  
Language Processing ◽  
Real World ◽  
Review Paper ◽  
General Concept ◽  
Research Trends ◽  
Human Intelligence

Artificial Intelligence is the combination of machine and human intelligence, which are in research trends from the last many years. Different Artificial Intelligence programs have become capable of challenging humans by providing Expert Systems, Neural Networks, Robotics, Natural Language Processing, Face Recognition and Speech Recognition. Artificial Intelligence brings a bright future for different technical inventions in various fields. This review paper shows the general concept of Artificial Intelligence and presents an impact of Artificial Intelligence in the present and future world.

scholarly journals New insights on real-world human face recognition.

2019 ◽  
Vol 148 (6) ◽  
pp. 994-1007 ◽  
Author(s):  
Christel Devue ◽  
Annabelle Wride ◽  
Gina M. Grimshaw
Keyword(s):  
Face Recognition ◽  
Real World ◽  
Human Face ◽  
Human Face Recognition

scholarly journals A grey area: How does image hue affect unfamiliar face matching?

2018 ◽  
Author(s):  
Anna K Bobak ◽  
Viktoria Roumenova Mileva ◽  
Peter Hancock
Keyword(s):  
Matching Task ◽  
Mixed Condition ◽  
Face Matching ◽  
Matching Test ◽  
Unfamiliar Face Matching ◽  
Unfamiliar Face ◽  
Matching Performance ◽  
Small Decline ◽  
Clear Shift

The role of image colour in face identification has received little attention in research despite the importance of identifying people from photographs in identity documents (IDs). Here, in two experiments, we investigated whether colour congruency of two photographs shown side by side affects face matching accuracy. Participants were presented with two images from the Models Face Matching Test (Experiment 1) and a newly devised matching task incorporating female faces (Experiment 2) and asked to decide whether they show the same person, or two different people. The photographs were either both in colour, both in grayscale, or mixed (one in grayscale and one in colour). Participants were more likely to accept a pair of images as a “match”, i.e. same person, in the mixed condition, regardless of whether the identity of the pair was the same or not. This demonstrates a clear shift in bias between “congruent” colour conditions and the mixed trials. In addition, there was a small decline in accuracy in the mixed condition, relative to when the images were presented in colour. Our study provides the first evidence that the hue of document photographs matters for face matching performance. This finding has important implications for the design and regulation of photographic ID worldwide.

Decision Deferral in a Human-AI Joint Face-Matching Task: Effects on Human Performance and Trust

2021 ◽  
Vol 65 (1) ◽  
pp. 638-642
Author(s):  
Pouria Salehi ◽  
Erin K. Chiou ◽  
Michelle Mancenido ◽  
Ahmadreza Mosallanezhad ◽  
Myke C. Cohen ◽  
...  
Keyword(s):  
Human Performance ◽  
Rate Sensitivity ◽  
Matching Task ◽  
Work Systems ◽  
Security Screening ◽  
Task Effects ◽  
Human Agent ◽  
Face Matching ◽  
Ethical And Legal Considerations ◽  
Process Component

This study investigates how human performance and trust are affected by the decision deferral rates of an AI-enabled decision support system in a high criticality domain such as security screening, where ethical and legal considerations prevent full automation. In such domains, deferring cases to a human agent becomes an essential process component. However, the systemic consequences of the rate of deferrals on human performance are unknown. In this study, a face-matching task with an automated face verification system was designed to investigate the effects of varying deferral rates. Results show that higher deferral rates are associated with higher sensitivity and higher workload, but lower throughput and lower trust in the AI. We conclude that deferral rates can affect performance and trust perceptions. The tradeoffs between deferral rate, sensitivity, throughput, and trust need to be considered in designing effective human-AI work systems.

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