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1-10 of 138 results for spatiotemporal attention

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Select article: Restoration of missing structural health monitoring data using spatiotemporal graph attention networks

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Research article

First published 2022-9

Restoration of missing structural health monitoring data using spatiotemporal graph attention networks

Jin Niu, Shunlong Li, Zhonglong Li

Structural Health Monitoring

Select article: ASISTGCRN: A novel approach to traffic prediction using attention-based spatiotemporal graph networks

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Research article

First published 2025

ASISTGCRN: A novel approach to traffic prediction using attention-based spatiotemporal graph networks

Fengjing Cai, Yue Wang, Wanghua Yu [...]

Proceedings of the Institution of Mechanical Engineers,Part D: Journal of Automobile Engineering

Select article: Spatiotemporal attention-based trend and residual decomposition model for multivariate time series anomaly detection

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Research article

First published 2026

Spatiotemporal attention-based trend and residual decomposition model for multivariate time series anomaly detection

Zhenhua Yu, Jiazhen Li, Lihua Sun [...]

Transactions of the Institute of Measurement and Control

Select article: Attention-enhanced spatiotemporal deep learning-based automatic warning model with uncertainty estimation in dam safety

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Research article

First published 2025

Attention-enhanced spatiotemporal deep learning-based automatic warning model with uncertainty estimation in dam safety

Hongchen Liu, Huaizhi Su, Soheila Kookalani [...]

Structural Health Monitoring

Select article: CMDRL: A cavity-aware deep reinforcement learning framework with spatiotemporal attention for 3D bin Packing

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Research article

First published 2026

CMDRL: A cavity-aware deep reinforcement learning framework with spatiotemporal attention for 3D bin Packing

Sirui Wang, Yunqing Rao, Nai Li [...]

Proceedings of the Institution of Mechanical Engineers,Part B: Journal of Engineering Manufacture

Select article: Attention-Based Spatiotemporal Adaptive Graph Diffusion Convolutional Network For Traffic Flow Prediction

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Research article

First published 2025-7

Attention-Based Spatiotemporal Adaptive Graph Diffusion Convolutional Network For Traffic Flow Prediction

Qiansong He, Dawen Xia, Jianjun Li [...]

Transportation Research Record: Journal of the Transportation Research Board

Select article: STGANT: Spatiotemporal Generative Attention Network with Adversarial Training for Intersection Vehicle Trajectory Prediction

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Research article

First published 2026-2

STGANT: Spatiotemporal Generative Attention Network with Adversarial Training for Intersection Vehicle Trajectory Prediction

Guohua Liang, Jianxu Shi, Yue Liu [...]

Transportation Research Record: Journal of the Transportation Research Board

Select article: Graph Convolution Network Combining Spatiotemporal Self-Attention and Mutual Information for Pedestrian-Trajectory Prediction

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Research article

First published 2025-2

Graph Convolution Network Combining Spatiotemporal Self-Attention and Mutual Information for Pedestrian-Trajectory Prediction

Chungang Hu, Zhuping Zhou, Zhenlin Yue [...]

Transportation Research Record: Journal of the Transportation Research Board

Select article: STC-PSSA: A New Model of Traffic Flow Forecasting Based on Spatiotemporal Convolution and Probabilistic Sparse Self-Attention

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Research article

First published 2024-12

STC-PSSA: A New Model of Traffic Flow Forecasting Based on Spatiotemporal Convolution and Probabilistic Sparse Self-Attention

Hong Zhang, Linbiao Chen, Xijun Zhang [...]

Transportation Research Record: Journal of the Transportation Research Board

Select article: Principal Component Analysis Embedded Temporal Attention Spatiotemporal Graph Convolutional Networks for Traffic Flow Prediction

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Research article

First published 2026-1

Principal Component Analysis Embedded Temporal Attention Spatiotemporal Graph Convolutional Networks for Traffic Flow Prediction

Hong Zhang, Yang Li, Xijun Zhang [...]

Transportation Research Record: Journal of the Transportation Research Board

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