AIMC Topic: Recognition, Psychology
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Can AI-generated faces serve as fillers in eyewitness lineups?
Memory (Hove, England)
Feb 20, 2025
To create a photo lineup for an eyewitness, police embed the suspect in a group of similar-looking individuals (i.e., fillers). If the witness selects the suspect from these photos of similar-looking people, then this provides evidence they remember ...
A temporal-spatial feature fusion network for emotion recognition with individual differences reduction.
Neuroscience
Jan 30, 2025
PURPOSE: In the context of EEG-based emotion recognition tasks, a conventional strategy involves the extraction of spatial and temporal features, subsequently fused for emotion prediction. However, due to the pronounced individual variability in EEG ...
Model-agnostic meta-learning for EEG-based inter-subject emotion recognition.
Journal of neural engineering
Jan 21, 2025
. Developing an efficient and generalizable method for inter-subject emotion recognition from neural signals is an emerging and challenging problem in affective computing. In particular, human subjects usually have heterogeneous neural signal charact...
An EEG-based emotion recognition method by fusing multi-frequency-spatial features under multi-frequency bands.
Journal of neuroscience methods
Jan 6, 2025
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...
Automated analysis of a novel object recognition test in mice using image processing and machine learning.
Behavioural brain research
Sep 30, 2024
The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers' obs...
The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates.
Annual review of vision science
Sep 2, 2024
Inferences made about objects via vision, such as rapid and accurate categorization, are core to primate cognition despite the algorithmic challenge posed by varying viewpoints and scenes. Until recently, the brain mechanisms that support these capab...
Improving the diagnostic value of lineup rejections.
Cognition
Aug 14, 2024
Erroneous eyewitness identification evidence is likely the leading cause of wrongful convictions. To minimize this error, scientists recommend collecting confidence. Research shows that eyewitness confidence and accuracy are strongly related when an ...
Emergence and reconfiguration of modular structure for artificial neural networks during continual familiarity detection.
Science advances
Jul 26, 2024
Advances in artificial intelligence enable neural networks to learn a wide variety of tasks, yet our understanding of the learning dynamics of these networks remains limited. Here, we study the temporal dynamics during learning of Hebbian feedforward...
Comparing human evaluations of eyewitness statements to a machine learning classifier under pristine and suboptimal lineup administration procedures.
Cognition
Jul 14, 2024
Recent work highlights the ability of verbal machine learning classifiers to distinguish between accurate and inaccurate recognition memory decisions (Dobbins, 2022; Dobbins & Kantner, 2019; Seale-Carlisle, Grabman, & Dodson, 2022). Given the surge o...
The attentive reconstruction of objects facilitates robust object recognition.
PLoS computational biology
Jun 13, 2024
Humans are extremely robust in our ability to perceive and recognize objects-we see faces in tea stains and can recognize friends on dark streets. Yet, neurocomputational models of primate object recognition have focused on the initial feed-forward p...
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