AIMC Topic: Cognition

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Learning Dual Encoding Model for Adaptive Visual Understanding in Visual Dialogue.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Nov 18, 2020
Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue task involves multiple rounds of dialogues which cover a broad range of visual content that could be related to any objects, relat...
Humans Machine Learning Image Processing, Computer-Assisted Natural Language Processing Semantics Cognition Models, Neurological
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Relationships between motor and cognitive functions and subsequent post-stroke mood disorders revealed by machine learning analysis.

Scientific reports Nov 11, 2020
Mood disorders (e.g. depression, apathy, and anxiety) are often observed in stroke patients, exhibiting a negative impact on functional recovery associated with various physical disorders and cognitive dysfunction. Consequently, post-stroke symptoms ...
Neural Networks, Computer Machine Learning Humans Male Movement Cognition Female Middle Aged Mood Disorders Stroke Rehabilitation Stroke Aged ROC Curve
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Artificial cognition: How experimental psychology can help generate explainable artificial intelligence.

Psychonomic bulletin & review Nov 6, 2020
Artificial intelligence powered by deep neural networks has reached a level of complexity where it can be difficult or impossible to express how a model makes its decisions. This black-box problem is especially concerning when the model makes decisio...
Cognition Psychology, Experimental Humans Artificial Intelligence
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Combining convolutional neural networks and cognitive models to predict novel object recognition in humans.

Journal of experimental psychology. Learning, memory, and cognition Nov 5, 2020
Object representations from convolutional neural network (CNN) models of computer vision (LeCun, Bengio, & Hinton, 2015) were used to drive a cognitive model of decision making, the linear ballistic accumulator (LBA) model (Brown & Heathcote, 2008), ...
Visual Perception Recognition, Psychology Humans Neural Networks, Computer Reaction Time Models, Psychological Cognition
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Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers.

Scientific reports Nov 2, 2020
Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to ...
Humans Magnetic Resonance Imaging Predictive Value of Tests Amyloid beta-Peptides ROC Curve Cognition Cerebral Amyloid Angiopathy Prognosis Aged, 80 and over Biomarkers Female Male Brain Aged Machine Learning Algorithms
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A robot that counts like a child: a developmental model of counting and pointing.

Psychological research Nov 1, 2020
In this paper, a novel neuro-robotics model capable of counting real items is introduced. The model allows us to investigate the interaction between embodiment and numerical cognition. This is composed of a deep neural network capable of image proces...
Child Humans Cognition Robotics
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Capturing human categorization of natural images by combining deep networks and cognitive models.

Nature communications Oct 27, 2020
Human categorization is one of the most important and successful targets of cognitive modeling, with decades of model development and assessment using simple, low-dimensional artificial stimuli. However, it remains unclear how these findings relate t...
Memory Cognition Pattern Recognition, Visual Models, Psychological Humans Judgment Decision Making Visual Cortex Deep Learning
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Resonator Networks, 1: An Efficient Solution for Factoring High-Dimensional, Distributed Representations of Data Structures.

Neural computation Oct 20, 2020
The ability to encode and manipulate data structures with distributed neural representations could qualitatively enhance the capabilities of traditional neural networks by supporting rule-based symbolic reasoning, a central property of cognition. Her...
Brain Animals Cognition Humans Neural Networks, Computer
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Resonator Networks, 2: Factorization Performance and Capacity Compared to Optimization-Based Methods.

Neural computation Oct 20, 2020
We develop theoretical foundations of resonator networks, a new type of recurrent neural network introduced in Frady, Kent, Olshausen, and Sommer (2020), a companion article in this issue, to solve a high-dimensional vector factorization problem aris...
Brain Humans Animals Cognition Neural Networks, Computer
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An Investigation of Speech Features, Plant System Alarms, and Operator-System Interaction for the Classification of Operator Cognitive Workload During Dynamic Work.

Human factors Oct 15, 2020
OBJECTIVE: To investigate speech features, human-machine alarms, and operator-system interaction for the estimation of cognitive workload in full-scale realistic simulated scenarios.
Cognition Workload Algorithms Speech Humans Machine Learning
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