AIMC Topic: Attention

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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...
Sleep Wake Disorders Electrooculography Sleep Stages Attention Polysomnography Algorithms Fourier Analysis Humans Adolescent Female Neural Networks, Computer Electroencephalography Child, Preschool Male Signal Processing, Computer-Assisted Child Electromyography
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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...
Accidents, Traffic Attention Automobile Driving Distracted Driving Humans Machine Learning Rural Population
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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...
Attention Pattern Recognition, Automated Neural Networks, Computer Algorithms Humans
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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) ...
Adult Male Deep Learning Language Female Young Adult Electroencephalography Attention Speech Perception Speech Computational Biology Models, Neurological Humans Brain
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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...
Humans Machine Learning Attention Perception Reading Nerve Net Child Dyslexia Brain Magnetic Resonance Imaging Brain Mapping Female Male
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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...
Semantics Natural Language Processing Data Mining Attention Humans Algorithms Models, Theoretical
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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...
Neural Networks, Computer Algorithms Attention Semantics Humans
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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...
Pattern Recognition, Automated Human Activities Humans Algorithms Neural Networks, Computer Deep Learning Attention
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Dual Attention Relation Network With Fine-Tuning for Few-Shot EEG Motor Imagery Classification.

IEEE transactions on neural networks and learning systems Oct 29, 2024
Recently, motor imagery (MI) electroencephalography (EEG) classification techniques using deep learning have shown improved performance over conventional techniques. However, improving the classification accuracy on unseen subjects is still challengi...
Neural Networks, Computer Algorithms Deep Learning Humans Brain-Computer Interfaces Signal-To-Noise Ratio Imagination Electroencephalography Signal Processing, Computer-Assisted Attention
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A Static Sign Language Recognition Method Enhanced with Self-Attention Mechanisms.

Sensors (Basel, Switzerland) Oct 29, 2024
For the current wearable devices in the application of cross-diversified user groups, it is common to face the technical difficulties of static sign language recognition accuracy attenuation, weak anti-noise ability, and insufficient system robustnes...
Pattern Recognition, Automated Sign Language Humans Wearable Electronic Devices Neural Networks, Computer Gestures Algorithms Attention
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