This article is about 8000 words long and is suggested to be read in 16 minutes. This article provides a detailed introduction to the relevant content from Graph to Graph Convolution. The author has recently reviewed several papers on Graphs and Graph Convolutional Neural Networks (GCNs) and is deeply impressed by their power. However, some … Read more
There is considerable research on using Graph Neural Networks (GNN) for computer vision (CV), but it typically revolves around point cloud data, with few directly addressing image data. Compared to CNNs, which treat an image as a grid, and Transformers, which flatten images into sequences, graph methods are more suitable for learning features of irregular … Read more
Machine Heart Column Author: Liu Zhongyu Source: Geetest (geetest_jy) Today I want to share with you about Graph Convolutional Networks. With the development of artificial intelligence, many people have heard of concepts such as machine learning, deep learning, and convolutional neural networks. However, Graph Convolutional Networks are not often mentioned. So, what are Graph Convolutional … Read more
This article is about 3200 words long and suggests a reading time of 6 minutes. Graph Neural Networks (GNN) are a type of deep learning method particularly adept at handling data with a graph structure. Graph Neural Networks (GNN) are a type of deep learning method particularly good at handling data with a graph structure. … Read more