AIMC Topic: Attention

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Attention-based hybrid deep learning model with CSFOA optimization and G-TverskyUNet3+ for Arabic sign language recognition.

Scientific reports Jun 26, 2025
Arabic sign language (ArSL) is a visual-manual language which facilitates communication among Deaf people in the Arabic-speaking nations. Recognizing the ArSL is crucial due to variety of reasons, including its impact on the Deaf populace, education,...
Humans Sign Language Algorithms Deep Learning Attention
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Shared and distinct neural signatures of feature and spatial attention.

NeuroImage Jun 18, 2025
The debate on whether feature attention (FA) and spatial attention (SA) share a common neural mechanism remains unresolved. Previous neuroimaging studies have identified fronto-parietal-temporal attention-related regions that exhibited consistent act...
Young Adult Adult Male Machine Learning Brain Female Nerve Net Visual Perception Space Perception Magnetic Resonance Imaging Brain Mapping Attention Humans
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Smartphone eye-tracking with deep learning: Data quality and field testing.

Behavior research methods Jun 18, 2025
Eye-tracking is widely used to measure human attention in research, commercial, and clinical applications. With the rapid advancements in artificial intelligence and mobile computing, deep learning algorithms for computer vision-based eye tracking ha...
Female Young Adult Adult Male Eye-Tracking Technology Deep Learning Humans Attention Data Accuracy Depression Eye Movements Smartphone
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Emergence of human-like attention and distinct head clusters in self-supervised vision transformers: A comparative eye-tracking study.

Neural networks : the official journal of the International Neural Network Society May 21, 2025
Visual attention models aim to predict human gaze behavior, yet traditional saliency models and deep gaze prediction networks face limitations. Saliency models rely on handcrafted low-level visual features, often failing to capture human gaze dynamic...
Head Fixation, Ocular Supervised Machine Learning Attention Humans Neural Networks, Computer Eye-Tracking Technology Deep Learning
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S2LIC: Learned image compression with the SwinV2 block, Adaptive Channel-wise and Global-inter attention Context.

Neural networks : the official journal of the International Neural Network Society May 19, 2025
Recently, deep learning technology has been successfully applied in the field of image compression, leading to superior rate-distortion performance. It is crucial to design an effective and efficient entropy model to estimate the probability distribu...
Data Compression Entropy Deep Learning Image Processing, Computer-Assisted Attention Neural Networks, Computer Algorithms Humans
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Multi-agent self-attention reinforcement learning for multi-USV hunting target.

Neural networks : the official journal of the International Neural Network Society May 16, 2025
A reinforcement learning (RL) method based on the multi-head self-attention (MSA) mechanism is proposed to solve the challenge of multiple unmanned surface vehicles (multi-USV) hunting target at the surface. The kinematic, dynamic, and environmental ...
Neural Networks, Computer Algorithms Robotics Attention Reinforcement, Psychology Humans
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Single-microphone deep envelope separation based auditory attention decoding for competing speech and music.

Journal of neural engineering May 7, 2025
In this study, we introduce an end-to-end single microphone deep learning system for source separation and auditory attention decoding (AAD) in a competing speech and music setup. Deep source separation is applied directly on the envelope of the obse...
Music Auditory Perception Acoustic Stimulation Speech Perception Humans Female Young Adult Speech Electroencephalography Attention Adult Male Deep Learning
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SMANet: A Model Combining SincNet, Multi-Branch Spatial-Temporal CNN, and Attention Mechanism for Motor Imagery BCI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 29, 2025
Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an ...
Movement Imagination Deep Learning Electroencephalography Signal Processing, Computer-Assisted Attention Brain-Computer Interfaces Signal-To-Noise Ratio Algorithms Adult Male Humans Neural Networks, Computer
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Self-supervised spatial-temporal contrastive network for EEG-based brain network classification.

Neural networks : the official journal of the International Neural Network Society Apr 28, 2025
Electroencephalogram (EEG)-based brain network analysis has shown promise in brain disease research by revealing the complex connectivity among brain regions. However, existing methods struggle to fully utilize the large amounts of unlabeled data to ...
Humans Neural Networks, Computer Epilepsy Attention Nerve Net Brain Electroencephalography
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MSCViT: A small-size ViT architecture with multi-scale self-attention mechanism for tiny datasets.

Neural networks : the official journal of the International Neural Network Society Apr 28, 2025
Vision Transformer (ViT) has demonstrated significant potential in various vision tasks due to its strong ability in modeling long-range dependencies. However, such success is largely fueled by training on massive samples. In real applications, the l...
Humans Neural Networks, Computer Algorithms Databases, Factual Attention
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