Few-shot image classification with graph neural network (GNN) is a hot topic in recent years. Most GNN-based approaches have achieved promising performance. These methods utilize node features or ...

This repository is the implementation of paper A Graph Neural Network for superpixel image classification by Jianwu Long , Zeran yan and Hongfa chen. The authors of the paper propose to solve the ...

Convolutional neural networks (CNNs) and Vision Transformers (ViTs) rely on a large number of parameters and complex network structures, which require significant computational costs, making them ...

Gori et al. (2005) proposed the concept of graph neural networks (GNNs) and designed a model that can directly process graph structure data based on research results in the field of neural networks.

DeepWalk first represents the network by a set of random walks starting from random nodes in the graph, so that a node's neighbor information can be reflected by the neighbor information in the random ...