AIMC Topic: Attention

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Super-resolution of 3D medical images by generative adversarial networks with long and short-term memory and attention.

Scientific reports
Since 3D medical imaging data is a string of sequential images, there is a strong correlation between consecutive images. Deep convolutional networks perform well in extracting spatial features, but are less capable for processing sequence data compa...

A fake news detection model using the integration of multimodal attention mechanism and residual convolutional network.

Scientific reports
To improve the accuracy and efficiency of fake news detection, this study proposes a deep learning model that integrates residual networks with attention mechanisms. Building on traditional convolutional neural networks, the model incorporates multi-...

EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation.

Scientific reports
Emotion recognition via EEG signals and facial analysis becomes one of the key aspects of human-computer interaction and affective computing, enabling scientists to gain insight into the behavior of humans. Classic emotion recognition methods usually...

Comparative analysis of attentional mechanisms in rice pest identification.

Scientific reports
Accurate detection of rice pests helps farmers take timely control measures. This study compares different attention mechanisms for rice pest detection in complex backgrounds and demonstrates that a human vision-inspired Bionic Attention (BA) mechani...

An interpretable stacking ensemble learning model for visual-manual distraction level classification for in-vehicle interactions.

Accident; analysis and prevention
Recognizing the level of driver distraction during the execution of secondary tasks within the intelligent cockpit is crucial for ensuring a seamless interaction between human drivers and intelligent vehicle systems. To address this issue, this paper...

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

Scientific reports
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,...

RIVA: Efficient relational inference with variate attention.

Neural networks : the official journal of the International Neural Network Society
Interactive systems are omnipresent across various domains, ranging from dynamic systems in physics to intricate societal dynamics. Relational inference aims to uncover implicit interactions between components based on observed system trajectories. E...

SimTA++: Simple attention neural network for clinical asynchronous time series.

Neural networks : the official journal of the International Neural Network Society
The task of modeling asynchronous time series data in clinical practice is a formidable challenge, made even more difficult by the multi-modal and irregular nature of real-world medical time series data. Despite advances in deep learning for sequenti...

Shared and distinct neural signatures of feature and spatial attention.

NeuroImage
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...

Smartphone eye-tracking with deep learning: Data quality and field testing.

Behavior research methods
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...