IEEE

A Graph Convolutional Encoder-Decoder Model for Methane Concentration Forecasting in Coal Mines

Abstract: Methane is one of the most dangerous gases produced in the process of coal mining. Because of its flammable and explosive characteristics, it has seriously threatened the life and property ...
Frontiers

RS-STGCN: Regional-Synergy Spatio-Temporal Graph Convolutional Network for emotion recognition

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 ...
IEEE

Self-Attention Based Multi-Scale Graph Auto-Encoder Network of 3D Meshes

Abstract: 3D meshes are fundamental data representations for capturing complex geometric shapes in computer vision and graphics applications. While Convolutional Neural Networks (CNNs) have excelled ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

The node embedding vectors of two different graphs were learned separately. Specifically, the upper part of the encoder was learned by the node features of the graph convolutional neural network layer ...
Scientific Research Publishing

A Combination Method of Stacked Convolutional Auto-Encoder and Selective Kernel Attention Mechanism for Image Classification

With the basic structure and parameters of the model remaining unchanged, this section analyzes and compares two types of network structures with input image sizes of 128 × 128 and 256 × 256. The ...