In this paper, a multichannel EEG emotion recognition method based on a novel dynamical graph convolutional neural networks (DGCNN) is proposed. The basic idea of the proposed EEG emotion recognition ...

Keywords: childhood seizure detection, graph convolutional network, adjacency matrix, EEG, multi-head attention Citation: Li Y, Yang Y, Song S, Wang H, Sun M, Liang X, Zhao P, Wang B, Wang N, Sun Q ...

Classifying complex knots in polymer science is a time-consuming task, often complicated by the close numerical values associated with knot invariants. Reported neural network models for knot ...

Keywords: EEG, driving fatigue detection, channel attention mechanism, graph convolutional network, spatial attention mechanism Citation: Liu H, Liu Q, Cai M, Chen K, Ma L, Meng W, Zhou Z and Ai Q ...

Based on the absolute Pearson's matrix of overall signals, the graph Laplacian of EEG electrodes was built up. The GCNs-Net constructed by graph convolutional layers learns the generalized features.

Toward the development of effective and efficient brain–computer interface (BCI) systems, precise decoding of brain activity measured by an electroencephalogram (EEG) is highly demanded. Traditional ...

The repository has the PyTorch codes to reproduce the results for our recently accepted paper, "Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network", in SEG ...