Zeng et al. (2020) proposed the hierarchical graph convolution (HGCN) network for classification tasks using topological relationships between each electrode, where power spectral density and ...

Extracting spatial–spectral joint features has become a critical approach for improving model classification performance in the field of hyperspectral image classification (HSIC). However, existing ...

To address the previously mentioned issue, we present a novel model in this paper, namely Graph Linear Convolution Pooling Network (GLCPN). The proposed GLCPN adopts the three-fold ideas. First, it ...

Learn More Pinterest today shared details about how it created PinSage, a graph convolutional network that can learn about things like nearby Pins, or nodes, in massive web-scale graphs.