Sports action estimation and recognition based on dynamic spatiotemporal graph convolution. [PDF]
BMC Sports Sci Med RehabilZhang F, Xiao H, Guo W.
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Multi-Sensor Spatiotemporal Feature Fusion for Early Warning of Cable Fires in Power Cable Tunnels. [PDF]
Sensors (Basel)Wang M, Li D, Sun X, Zheng H.
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Deep Learning-Based Automated Clinical Gait Assessment From Kinematic Data in People With Stroke: Development and Validation Study. [PDF]
JMIR Rehabil Assist TechnolGu Z +7 more
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Graphitic Carbon Nitride (g-C<sub>3</sub>N<sub>4</sub>)-Catalysed Green Synthesis of Heterocycles: Progress, Mechanistic Insights, and Future Perspectives. [PDF]
MoleculesBarasarathi J +6 more
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Universum Inspired Graph Contrast Learning for Major Depressive Disorder Identification: In Functional Brain Network View. [PDF]
CNS Neurosci TherQin H +6 more
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KEMFF: A Knowledge-Enhanced and Multidimensional Feature Fusion Model for Aspect-Based Sentiment Analysis. [PDF]
Entropy (Basel)Yang S, Liu P, Zhu W.
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Adolescent depression recognition and symptom prediction based on multi-view EEG network: an exploratory study. [PDF]
Front PsychiatryZhao Y +10 more
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GCN-ABFT: Low-Cost Online Error Checking for Graph Convolutional Networks
Graph convolutional networks (GCNs) are popular for building machine-learning application for graph-structured data. This widespread adoption led to the development of specialized GCN hardware accelerators.
Peltekis, Christodoulos +1 more
core
Patient-Specific Spatio-Temporal False Data Injection Attack Detection for IoMT Using a Graph-GRU Digital Twin and Kalman Innovation Features. [PDF]
Bioengineering (Basel)Alkhammash EH +3 more
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DHA-eGCN: Differential Hyperedge Attention-Enhanced Graph Convolution Network for Skeleton-Based Human Action Recognition. [PDF]
Sensors (Basel)Nugroho OIA, Lie WN.
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