Recently, Graph Convolution Network (GCN) and Temporal Convolution Network (TCN) are introduced into traffic prediction and achieve state-of-the-art performance due to their good ability for modeling ...

Abstract: Electroencephalograph (EEG) emotion recognition plays an important role in the brain-computer interface (BCI) field. However, most of recent methods adopted shallow graph neural networks ...

This repository contains the implementation of DSTFGCN, a deep learning model for traffic flow forecasting.

Visual multi-vessel tracking is critical for intelligent maritime surveillance yet challenging due to the complexity of efficiently modeling rigid vessel structures across diverse scales and ...

Deconvolution as a research area focuses on developing and analyzing mathematical and computational methods to invert convolution operations, typically to recover latent signals, images, or ...

School of Information Engineering, Shanghai Maritime University, Shanghai 201306, P. R. China ...

The sensor payload (thermopile + VL53L8CX ToF) is carried by a rigid pan-tilt assembly driven by two NEMA 17 stepper motors ...

Basquiat’s Headstrong is the first solo presentation of the artist at a museum in Scandinavia. The exhibition brings together ...