Tag: graph convolutional network

Researchers have unveiled an explainable deep learning framework that detects insect crop pests in real time with up to 98 ...

Researchers have developed a graph-based deep learning network that decodes imagined movements from EEG signals with accuracies of up to ...

Researchers combined a graph autoencoder, an attention-equipped graph convolutional network, and a slime-mould-inspired optimizer to locate hidden faults in smart ...

Researchers have unveiled EEG-UDAF, an unsupervised domain adaptation framework that fuses dual-view frequency features with spatio-temporal modeling to recognize emotions ...

Researchers in Hangzhou have developed MGCRN, a graph-based recurrent neural network that maintains high forecasting accuracy on spatio-temporal data even ...

A multicenter study shows a hybrid deep learning model combining CNN and graph convolutional networks can predict malignancy in BI-RADS ...

Researchers at the University of Tabriz have developed GCAT, a graph-convolutional adversarial transformer that detects anomalies in multivariate sensor data ...

A new hybrid model called TG-Parser combines Transformer encoders with graph convolutional networks to achieve record-setting accuracy in English grammatical ...

Researchers have built an end-to-end deep learning framework that combines 3D hand pose estimation with hand action recognition from egocentric ...

Researchers have introduced RPGCN, a relation-preserving graph convolutional network that combats oversmoothing and relational dilution to outperform state-of-the-art baselines across ...