Abstract: Graph convolutional networks demonstrate advantages such as low sample requirements and strong global information modeling capabilities in the semantic segmentation of synthetic aperture ...

The code in this repository implements an efficient generalization of the popular Convolutional Neural Networks (CNNs) to arbitrary graphs, presented in our paper: Michaël Defferrard, Xavier Bresson, ...

In the AI field, new models are being constantly released and every other week, a new AI image model comes out on top. So in this article, we have compiled a list of the best AI image generators which ...

Decoding emotional states from electroencephalography (EEG) signals is a fundamental goal in affective neuroscience. This endeavor requires accurately modeling the complex spatio-temporal dynamics of ...

Brain-computer interfaces (BCIs) are advanced and innovative systems that enable direct communication between humans and external devices by utilizing data encoded in the brain activity (Shi et al., ...

Abstract: Graph convolutional networks (GCNs) have demonstrated remarkable performance in hyperspectral image classification and remote sensing scene recognition. However, their application to ...

Graph-based image segmentation frames an image as a weighted graph in which pixels or regions correspond to nodes, and edges encode similarity or affinity between neighbouring elements. By formulating ...