A Spatial|Temporal Attention Multi|Graph Convolution ...

A Spatial-Temporal Attention Multi-Graph Convolution Network for ...

Title:A Spatial-Temporal Attention Multi-Graph Convolution Network for Ride-Hailing Demand Prediction Based on Periodicity with Offset.

Multi-Attention Based Spatial-Temporal Graph Convolution ...

Traffic forecasting is a great challenge to effectively extract complex spatio-temporal patterns due to the dynamic and nonlinear spatio-temporal ...

Multiscale spatial temporal attention graph convolution network for ...

We propose a multiscale spatial temporal attention graph convolution network (MSTA-GCN) to capture and cluster the features of the human skeleton.

Multi-scale spatial–temporal attention graph convolutional networks ...

This paper proposes a lightweight multi-scale spatio-temporal attention graph convolutional network (MS-STAGCN) to efficiently utilize skeleton data to ...

Spatial Temporal Attention Graph Convolutional Networks with ...

We propose spatial- temporal attention graph convolutional networks (STA-GCN). It ac- quires an attention edge that represents a static relationship between.

Spatiotemporal adaptive attention graph convolution network for city ...

In this paper, we propose a novel deep learning model, the spatiotemporal adaptive attention graph convolution model, for city-level air quality prediction.

A Spatial-Temporal Attention Multi-Graph Convolution Network for ...

A spatial-temporal attention multi-graph convolution network (STA-MGCN) and a novel approach which considers the transportation feature of periodicity with ...

Multi-Scale Spatial Temporal Graph Convolutional Network ... - arXiv

Abstract page for arXiv paper 2206.13028: Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition.

Spatial-Temporal Attention Graph Convolution Network on Edge ...

In this paper, we propose a Spatial-Temporal Attention Graph Convolution Network on Edge Cloud model (STAGCN-EC).

Multi-Attention Based Spatial-Temporal Graph Convolution ...

A spatial-temporal graph convolution network based on multi-attention mechanism is proposed to predict long-term traffic conditions of different locations ...

Attention Based Spatial-Temporal Graph Convolutional Networks for ...

ASTGCN mainly consists of three independent components to respectively model three temporal properties of traffic flows, i.e., recent, daily-periodic and weekly ...

Multi-View Spatial-Temporal Graph Convolutional Networks With ...

In addition, attention mechanism is employed for capturing the most relevant spatial-temporal information for sleep stage classification. Finally, domain ...

Attention Based Spatial-Temporal Graph Convolutional Networks for ...

In this paper, we propose a novel attention based spatial-temporal graph con- volutional network (ASTGCN) model to solve traffic flow forecasting problem.

Spatial-Temporal Attention Mechanism and Graph Convolutional ...

This paper proposes a human-in-loop Spatial-Temporal Attention Mechanism with Graph Convolutional Network (STAGCN) model to explore the spatial-temporal ...

Spatial–temporal combination and multi-head flow-attention network ...

proposed spatio-temporal graph convolutional networks (STGCN), which uses graph convolution to capture spatial dependence and uses one- ...

Multi‐stream adaptive spatial‐temporal attention graph ...

Skeleton-based action recognition algorithms have been widely applied to human action recognition. Graph convolutional networks (GCNs) ...

STA-GCN: Spatial-Temporal Self-Attention Graph Convolutional ...

This paper proposes a spatial–temporal prediction model that can capture the dynamic spatial–temporal characteristics of traffic flow.

Multiple Information Spatial–Temporal Attention based Graph ...

Cui Z., Henrickson K., Ke R., Wang Y., Traffic graph convolutional recurrent neural network: A deep learning framework for network-scale traffic ...

Multiple Information Spatial-Temporal Attention Based Graph ...

Download Citation | On Feb 1, 2023, Shiming Tao and others published Multiple Information Spatial-Temporal Attention Based Graph Convolution ...

Temporal Attention Graph Convolution Network for Traffic Forecasting

In this paper, we propose a spatial–temporal attention graph convolution network (STAGCN), which acquires a static graph and a dynamic graph from data without ...