AIMC Topic: Attention

Clear Filters Showing 541 to 550 of 642 articles

Neural evidence for attentional resource allocation to postural control using brain-body imaging.

Behavioural brain research
OBJECTIVE: To examine whether bipedal stance (quiet standing) requires more attentional resources than sitting during a concurrent cognitive task.

Functional Consequences of Tinnitus in Military Service Members.

American journal of audiology
PURPOSE: Numerous individuals in the United States are bothered enough by tinnitus that it affects normal daily activities, including sleep and concentration. There is a high prevalence of self-reported bothersome tinnitus in the U.S. military, and t...

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
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...

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
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...

Multi-agent self-attention reinforcement learning for multi-USV hunting target.

Neural networks : the official journal of the International Neural Network Society
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 ...

Enhancing realism in LiDAR scene generation with CSPA-DFN and linear cross-attention via Diffusion Transformer model.

Neural networks : the official journal of the International Neural Network Society
Point cloud diffusion models have found extensive applications in autonomous driving and robotics. However, there is still a big gap between their generated LiDAR scene samples and real-world data in terms of visual quality. This discrepancy primaril...

Urinary Metabolic Biomarkers of Attentional Control in Children With Attention-Deficit/Hyperactivity Disorder: A Dimensional Approach Through H NMR-Based Metabolomics.

NMR in biomedicine
Enhancing the understanding of attention-deficit/hyperactivity disorder (ADHD) by linking biological processes with behavioral manifestations is a primary objective of the Research Domain Criteria (RDoC) framework, which aims to transcend traditional...

MT-RCAF: A Multi-Task Residual Cross Attention Framework for EEG-based emotion recognition and mood disorder detection.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prolonged abnormal emotions can gradually evolve into mood disorders such as anxiety and depression, making it critical to study the relationship between emotions and mood disorders to explore the causes of mood disorders. E...

Enhanced Graph Attention Network by Integrating Transformer for Epileptic EEG Identification.

International journal of neural systems
Electroencephalography signal classification is essential for the diagnosis and monitoring of neurological disorders, with significant implications for patient treatment. Despite the progress made, existing methods face challenges such as capturing t...

Artificial intelligence automated solution for hazard annotation and eye tracking in a simulated environment.

Accident; analysis and prevention
High-fidelity simulators and sensors are commonly used in research to create immersive environments for studying real-world problems. This setup records detailed data, generating large datasets. In driving research, a full-scale car model repurposed ...