CNN2GNN: How to Bridge CNN with GNN

arXiv:2404.14822v1 Announce Type: new
Abstract: Although the convolutional neural network (CNN) has achieved excellent performance in vision tasks by extracting the intra-sample representation, it will take a higher training expense because of stacking numerous convolutional layers. Recently, as the bilinear models, graph neural networks (GNN) have succeeded in exploring the underlying topological relationship among the graph data with a few graph neural layers. Unfortunately, it cannot be directly utilized on non-graph data due to the lack of graph structure and …

abstract arxiv bridge cnn convolutional neural network cs.ai cs.cv gnn graph graph neural networks network networks neural network neural networks performance relationship representation sample tasks training type vision will