HetGAT: a heterogeneous graph attention network for freeway traffic speed prediction
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Spatial-Frequency Attention Network for Crowd Counting
Sign Up to like & getrecommendations! 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
Altered attention network in paratroopers exposed to repetitive subconcussion: evidence based on behavioral and ERP results.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of neurotrauma"
DOI: 10.1089/neu.2021.0253
Abstract: Cognitive impairment caused by repetitive subconcussion has been received increasing attention in recent years. While the dysfunction of attention has been confirmed by neuropsychological research using scales, there is no event-related potentials (ERPs) research. Attention… read more here.
Keywords: attention network; repetitive subconcussion; subconcussion; group ... See more keywords
CasANGCL: pre-training and fine-tuning model based on cascaded attention network and graph contrastive learning for molecular property prediction
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac566
Abstract: MOTIVATION Molecular property prediction is a significant requirement in AI-driven drug design and discovery, aiming to predict the molecular property information (e.g. toxicity) based on the mined biomolecular knowledge. Although graph neural networks have been… read more here.
Keywords: attention network; cascaded attention; network; molecular property ... See more keywords
AGAT-PPIS: a novel protein-protein interaction site predictor based on augmented graph attention network with initial residual and identity mapping.
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad122
Abstract: Identifying protein-protein interaction (PPI) site is an important step in understanding biological activity, apprehending pathological mechanism and designing novel drugs. Developing reliable computational methods for predicting PPI site as screening tools contributes to reduce lots… read more here.
Keywords: protein protein; attention network; graph attention; site ... See more keywords
DeepIDP-2L: protein intrinsically disordered region prediction by combining convolutional attention network and hierarchical attention network
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab810
Abstract: MOTIVATION Intrinsically disordered regions (IDRs) are widely distributed in proteins. Accurate prediction of IDRs is critical for the protein structure and function analysis. The IDRs are divided into long disordered regions (LDRs) and short disordered… read more here.
Keywords: attention network; disordered regions; ldrs sdrs; attention ... See more keywords
Regional cerebral hypoperfusion after acute sleep deprivation
Sign Up to like & getrecommendations! Published in 2019 at "Medicine"
DOI: 10.1097/md.0000000000014008
Abstract: Abstract Previous neuroimaging studies have shown that functional changes occur after acute sleep deprivation, which suggest detrimental effects of a lack of sleep on the intrinsic functional architecture of the brain. We aimed to identify… read more here.
Keywords: acute sleep; attention network; sleep deprivation; regional cerebral ... See more keywords
The Attention Network Test in Parkinson and Lewy Body Disease: A Systematic Review
Sign Up to like & getrecommendations! Published in 2022 at "Cognitive and Behavioral Neurology"
DOI: 10.1097/wnn.0000000000000292
Abstract: Background: The Attention Network Test (ANT) is a well-established measure of efficiency for the alerting, orienting, and executive attentional networks. However, its novel application in Parkinson disease (PD) and Lewy body dementia (LBD) research more… read more here.
Keywords: network; network test; lbd groups; attention network ... See more keywords
Matching Descriptions to Spatial Entities Using a Siamese Hierarchical Attention Network
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2837666
Abstract: Spatial entity descriptions are written in natural language based on the observations and understanding of spatial entities and often contain rich semantic information beyond GIS systems. Therefore, entity descriptions must be related to spatial entities… read more here.
Keywords: hierarchical attention; siamese hierarchical; attention network; spatial entities ... See more keywords