AIMC Topic: Attention

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Personalized multi-head self-attention network for news recommendation.

Neural networks : the official journal of the International Neural Network Society Oct 22, 2024
With the rapid explosion of online news and user population, personalized news recommender systems have proved to be efficient ways of alleviating information overload problems by suggesting information which attracts users in line with their tastes....
Humans Attention Neural Networks, Computer
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Hypergraph contrastive attention networks for hyperedge prediction with negative samples evaluation.

Neural networks : the official journal of the International Neural Network Society Oct 19, 2024
Hyperedge prediction aims to predict common relations among multiple nodes that will occur in the future or remain undiscovered in the current hypergraph. It is traditionally modeled as a classification task, which performs hypergraph feature learnin...
Reproducibility of Results Attention Neural Networks, Computer Algorithms Humans
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Attention Induced Dual Convolutional-Capsule Network (AIDC-CN): A deep learning framework for motor imagery classification.

Computers in biology and medicine Oct 18, 2024
In recent times, Electroencephalography (EEG)-based motor imagery (MI) decoding has garnered significant attention due to its extensive applicability in healthcare, including areas such as assistive robotics and rehabilitation engineering. Neverthele...
Humans Neural Networks, Computer Brain-Computer Interfaces Electroencephalography Signal Processing, Computer-Assisted Brain Imagination Attention Deep Learning
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Dictionary trained attention constrained low rank and sparse autoencoder for hyperspectral anomaly detection.

Neural networks : the official journal of the International Neural Network Society Oct 11, 2024
Dictionary representations and deep learning Autoencoder (AE) models have proven effective in hyperspectral anomaly detection. Dictionary representations offer self-explanation but struggle with complex scenarios. Conversely, autoencoders can capture...
Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Attention Algorithms Hyperspectral Imaging
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Classification of Internal and External Distractions in an Educational VR Environment Using Multimodal Features.

IEEE transactions on visualization and computer graphics Oct 11, 2024
Virtual reality (VR) can potentially enhance student engagement and memory retention in the classroom. However, distraction among participants in a VR-based classroom is a significant concern. Several factors, including mind wandering, external noise...
Electroencephalography Attention Computer Graphics Humans Eye-Tracking Technology Brain Virtual Reality Neural Networks, Computer Female Adult Machine Learning Young Adult Male
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ExGAT: Context extended graph attention neural network.

Neural networks : the official journal of the International Neural Network Society Oct 5, 2024
As an essential concept in attention, context defines the overall scope under consideration. In attention-based GNNs, context becomes the set of representation nodes of graph embedding. Current approaches choose immediate neighbors of the target or i...
Humans Computer Simulation Attention Neural Networks, Computer Algorithms
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BAB-GSL: Using Bayesian influence with attention mechanism to optimize graph structure in basic views.

Neural networks : the official journal of the International Neural Network Society Oct 5, 2024
In recent years, Graph Neural Networks (GNNs) have garnered significant attention, with a notable focus on Graph Structure Learning (GSL), a branch dedicated to optimizing graph structures to enhance network training performance. Current GSL methods ...
Humans Algorithms Computer Graphics Neural Networks, Computer Bayes Theorem Machine Learning Attention
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ECG classification based on guided attention mechanism.

Computer methods and programs in biomedicine Oct 3, 2024
BACKGROUND AND OBJECTIVE: Integrating domain knowledge into deep learning models can improve their effectiveness and increase explainability. This study aims to enhance the classification performance of electrocardiograms (ECGs) by customizing specif...
Wolff-Parkinson-White Syndrome Attention Atrial Fibrillation Electrocardiography Signal Processing, Computer-Assisted Algorithms Deep Learning Humans
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An integrated framework for driving risk evaluation that combines lane-changing detection and an attention-based prediction model.

Traffic injury prevention Oct 2, 2024
OBJECTIVE: In recent years, the increase in traffic accidents has emerged as a significant social issue that poses a serious threat to public safety. The objective of this study is to predict risky driving scenarios to improve road safety.
Humans Machine Learning Algorithms Accidents, Traffic Attention Automobile Driving Risk Assessment Models, Theoretical
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Predicting the effectiveness of binaural beats on working memory.

Neuroreport Sep 30, 2024
Working memory is vital for short-term information processing. Binaural beats can enhance working memory by improving attention and memory consolidation through neural synchronization. However, individual differences in cognitive and neuronal functio...
Brain Waves Auditory Perception Attention Acoustic Stimulation Young Adult Brain Humans Electroencephalography Machine Learning Adult Memory, Short-Term Female Male
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