AIMC Topic: Attention

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MACNet: A Multidimensional Attention-Based Convolutional Neural Network for Lower-Limb Motor Imagery Classification.

Sensors (Basel, Switzerland) Nov 28, 2024
Decoding lower-limb motor imagery (MI) is highly important in brain-computer interfaces (BCIs) and rehabilitation engineering. However, it is challenging to classify lower-limb MI from electroencephalogram (EEG) signals, because lower-limb motions (L...
Signal Processing, Computer-Assisted Attention Brain-Computer Interfaces Imagination Brain Lower Extremity Electroencephalography Humans Neural Networks, Computer Algorithms
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The use of machine learning to understand the role of visual attention in multi-attribute choice.

Acta psychologica Nov 22, 2024
Whether eye movements (as a measure of visual attention) contribute to the understanding of how multi-attribute decisions are made, is still a matter of debate. In this study, we show how machine learning methods can be used to separate the effects o...
Humans Machine Learning Attention Visual Perception Female Choice Behavior Eye-Tracking Technology Young Adult Adolescent Adult Eye Movements
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AFSleepNet: Attention-Based Multi-View Feature Fusion Framework for Pediatric Sleep Staging.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Nov 15, 2024
The widespread prevalence of sleep problems in children highlights the importance of timely and accurate sleep staging in the diagnosis and treatment of pediatric sleep disorders. However, most existing sleep staging methods rely on one-dimensional r...
Electrooculography Sleep Stages Child, Preschool Polysomnography Child Humans Female Fourier Analysis Neural Networks, Computer Electroencephalography Male Sleep Wake Disorders Algorithms Adolescent Signal Processing, Computer-Assisted Electromyography Attention
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A machine learning approach to understanding the road and traffic environments of crashes involving driver distraction and inattention (DDI) on rural multilane highways.

Journal of safety research Nov 14, 2024
INTRODUCTION: Driver distraction and inattention (DDI) are major causes of road crashes, especially on rural highways. However, not all instances of distracted or inattentive driving lead to crashes. Previous studies indicate that DDI-related driving...
Humans Attention Automobile Driving Distracted Driving Machine Learning Rural Population Accidents, Traffic
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UMS-ODNet: Unified-scale domain adaptation mechanism driven object detection network with multi-scale attention.

Neural networks : the official journal of the International Neural Network Society Nov 12, 2024
Unsupervised domain adaptation techniques improve the generalization capability and performance of detectors, especially when the source and target domains have different distributions. Compared with two-stage detectors, one-stage detectors (especial...
Algorithms Attention Pattern Recognition, Automated Humans Neural Networks, Computer
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Deep-learning models reveal how context and listener attention shape electrophysiological correlates of speech-to-language transformation.

PLoS computational biology Nov 11, 2024
To transform continuous speech into words, the human brain must resolve variability across utterances in intonation, speech rate, volume, accents and so on. A promising approach to explaining this process has been to model electroencephalogram (EEG) ...
Brain Language Female Humans Models, Neurological Deep Learning Electroencephalography Speech Attention Young Adult Computational Biology Adult Male Speech Perception
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Distinct connectivity patterns between perception and attention-related brain networks characterize dyslexia: Machine learning applied to resting-state fMRI.

Cortex; a journal devoted to the study of the nervous system and behavior Nov 8, 2024
Diagnosis of dyslexia often occurs in late schooling years, leading to academic and psychological challenges. Furthermore, diagnosis is time-consuming, costly, and reliant on arbitrary cutoffs. On the other hand, automated algorithms hold great poten...
Perception Nerve Net Reading Dyslexia Magnetic Resonance Imaging Brain Mapping Attention Female Male Humans Child Machine Learning Brain
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Semantic-guided attention and adaptive gating for document-level relation extraction.

Scientific reports Nov 4, 2024
In natural language processing, document-level relation extraction is a complex task that aims to predict the relationships among entities by capturing contextual interactions from an unstructured document. Existing graph- and transformer-based model...
Attention Semantics Models, Theoretical Natural Language Processing Data Mining Humans Algorithms
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GradToken: Decoupling tokens with class-aware gradient for visual explanation of Transformer network.

Neural networks : the official journal of the International Neural Network Society Nov 1, 2024
Transformer networks have been widely used in the fields of computer vision, natural language processing, graph-structured data analysis, etc. Subsequently, explanations of Transformer play a key role in helping humans understand and analyze its deci...
Humans Neural Networks, Computer Algorithms Attention Semantics
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DiamondNet: A Neural-Network-Based Heterogeneous Sensor Attentive Fusion for Human Activity Recognition.

IEEE transactions on neural networks and learning systems Oct 29, 2024
With the proliferation of intelligent sensors integrated into mobile devices, fine-grained human activity recognition (HAR) based on lightweight sensors has emerged as a useful tool for personalized applications. Although shallow and deep learning al...
Humans Attention Pattern Recognition, Automated Human Activities Neural Networks, Computer Algorithms Deep Learning
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