IEEE

Bi-STDGCN: A Bidirectional Spatiotemporal Diffusion Graph Convolutional Network with Multi ...

Abstract: Accurate traffic flow prediction is a key application in Internet of Things (IoT)-enabled intelligent transportation systems (ITS). However, complex spatiotemporal dependencies and ...
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

LeaGCN: A Learnable Graph Convolutional Network with Temporal Attention for Traffic Forecasting

Abstract: Accurate traffic flow prediction is critical for intelligent transportation systems but remains a significant challenge due to complex and dynamic spatio-temporal dependencies. While Graph ...
Frontiers

Multi-Scale graph wavelet convolutional network for hyperspectral image classification

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
The New York Times

ESPN, NFL formally announce deal: NFL media assets to network, 10% equity to league

In a blockbuster trade, the NFL and ESPN formally announced their billion-dollar agreement that will see ESPN acquire NFL media assets — including NFL Network, linear distribution rights to RedZone ...
C&EN

Graph Convolutional Neural Network-Enabled Frontier Molecular Orbital Prediction: A Case ...

Department of Chemistry and Biochemistry, University of Wisconsin─Eau Claire, Eau Claire, Wisconsin 54702, United States ...