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...
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-...
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...
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...
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...
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,...
Neural networks : the official journal of the International Neural Network Society
Jun 21, 2025
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...
Neural networks : the official journal of the International Neural Network Society
Jun 20, 2025
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...
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...
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...
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