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   Articles with "attention network" as a keyword



HetGAT: a heterogeneous graph attention network for freeway traffic speed prediction

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recommendations! Published in 2021 at "Journal of Ambient Intelligence and Humanized Computing"

DOI: 10.1007/s12652-020-02807-0

Abstract: As an essential part of the modern intelligent traffic management system, traffic speed prediction is a challenging task. In recent studies, deep neural networks (LSTM and WaveNet) and graph neural networks (GCN and GNN) have… read more here.

Keywords: speed; attention network; graph attention; graph ... See more keywords

Both dorsal and ventral attention network nodes are implicated in exogenously driven visuospatial anticipation

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recommendations! Published in 2019 at "Cortex"

DOI: 10.1016/j.cortex.2019.02.031

Abstract: Neuroimaging and transcranial magnetic stimulation (TMS) studies have implicated a dorsal fronto-parietal network in endogenous attention control and a more ventral set of areas in exogenous attention shifts. However, the extent and circumstances under which… read more here.

Keywords: attention network; dorsal ventral; ventral attention; attention ... See more keywords

SAN-T2T: An automated table-to-text generator based on selective attention network

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recommendations! Published in 2023 at "Natural Language Engineering"

DOI: 10.1017/s135132492300013x

Abstract: Table-to-text generation aims to generate descriptions for structured data (i.e., tables) and has been applied in many fields like question-answering systems and search engines. Current approaches mostly use neural language models to learn alignment between… read more here.

Keywords: selective attention; attention network; table text; attention ... See more keywords

Visual awareness sharpens and accelerates attentional sampling through enhancing inhibitory neural modulation in the attention network

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recommendations! Published in 2025 at "Nature Communications"

DOI: 10.1038/s41467-025-64987-7

Abstract: Attentional sampling, orchestrated by neural oscillations within the frontoparietal attention network, sequentially focuses on stimuli in a dynamic pattern, thereby enhancing the efficiency of attentional selection. However, the role of conscious awareness in this default… read more here.

Keywords: attention network; inhibitory neural; awareness; attentional sampling ... See more keywords

Automated seizure detection in epilepsy using a novel dynamic temporal-spatial graph attention network

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-01015-0

Abstract: Epilepsy is a neurological disorder characterized by recurrent seizures caused by excessive electrical discharges in brain cells, posing significant diagnostic and therapeutic challenges. Dynamic brain network analysis via electroencephalography (EEG) has emerged as a powerful… read more here.

Keywords: graph attention; attention; seizure; attention network ... See more keywords

UANV: UNet-based attention network for thoracolumbar vertebral compression fracture angle measurement

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-03514-6

Abstract: Kyphosis is a prevalent spinal condition where the spine curves in the sagittal plane, resulting in spine deformities. Curvature estimation provides a powerful index to assess the deformation severity of scoliosis. In current clinical diagnosis,… read more here.

Keywords: angle measurement; attention; attention network; network ... See more keywords

High-performance parallel multi-scale attention network with explainable AI for intelligent diagnosis of leaf diseases in agricultural systems

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-26144-4

Abstract: Detecting leaf diseases is crucial for ensuring crop health and boosting agricultural productivity. An advanced deep learning-based framework is introduced for cassava and groundnut leaf disease detection, incorporating a suite of innovative techniques to enhance… read more here.

Keywords: leaf diseases; attention network; network; leaf ... See more keywords

A paired multi-scale attention network for liver tumor segmentation in 99mTc-MAA SPECT/CT imaging

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-94195-8

Abstract: Automatic liver tumor segmentation using Single-Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) provides detailed insights that facilitate accurate tumor targeting and effective treatment planning. However, challenges such as spill-out can distort tumor size, which complicates accurate… read more here.

Keywords: tumor segmentation; scale attention; liver tumor; multi scale ... See more keywords

Assessment of the urban habitat quality service functions and their drivers based on the fusion module of graph attention network and residual network

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recommendations! Published in 2024 at "International Journal of Digital Earth"

DOI: 10.1080/17538947.2024.2306310

Abstract: ABSTRACT Land use/cover change is a major cause of ecological degradation. Reliable LUCC data are essential for evaluating habitat quality. The current method of surface cover classification based on the convolutional neural networks (CNNs) is… read more here.

Keywords: graph attention; habitat quality; attention network; network ... See more keywords

Solving Quantum Many-Particle Models with Graph Attention Network

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recommendations! Published in 2024 at "Chinese Physics Letters"

DOI: 10.1088/0256-307x/41/3/030202

Abstract: Deep learning methods have been shown to be effective in representing ground-state wavefunctions of quantum many-body systems, however the existing approaches cannot be easily used for non-square like or large systems. Here, we propose a… read more here.

Keywords: graph attention; quantum many; attention network; solving quantum ... See more keywords

Spatial-Frequency Attention Network for Crowd Counting

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recommendations! Published in 2022 at "Big data"

DOI: 10.1089/big.2022.0039

Abstract: Counting the number of people in crowded scenarios is a crucial task in video surveillance and urban security system. Widely deployed surveillance cameras provide big data for training, a compelling deep learning-based counting network. However,… read more here.

Keywords: frequency attention; frequency; attention network; spatial frequency ... See more keywords