AIMC Topic: Recognition, Psychology

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AI-generated estimates of familiarity, concreteness, valence, and arousal for over 100,000 Spanish words.

Quarterly journal of experimental psychology (2006)
This study investigates whether estimates of familiarity, valence, arousal, and concreteness based on artificial intelligence (AI) are useful alternatives to word counts and human ratings in Spanish. We replicate and extend previous findings in Engli...

Automated analysis of a novel object recognition test in mice using image processing and machine learning.

Behavioural brain research
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
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
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
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
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
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...

An analysis of information segregation in parallel streams of a multi-stream convolutional neural network.

Scientific reports
Visual information is processed in hierarchically organized parallel streams in the primate brain. In the present study, information segregation in parallel streams was examined by constructing a convolutional neural network with parallel architectur...

A deep learning-based dynamic deformable adaptive framework for locating the root region of the dynamic flames.

PloS one
Traditional optical flame detectors (OFDs) in flame detection are susceptible to environmental interference, which will inevitably cause detection errors and miscalculations when confronted with a complex environment. The conventional deep learning-b...

A neurocomputational model of decision and confidence in object recognition task.

Neural networks : the official journal of the International Neural Network Society
How does the brain process natural visual stimuli to make a decision? Imagine driving through fog. An object looms ahead. What do you do? This decision requires not only identifying the object but also choosing an action based on your decision confid...