Dest-ResNet is a sequence learning framework that jointly deals with two sequences in different modalities, i.e., the traffic speed sequence and the query sequence. The motivation behind Dest-ResNet attempts to learn a residual network to amend the errors caused when the unimodal in- formation is learned individually.
Then Dest-ResNet (Deep spatiotemporal Residual Network) is proposed for hotspot traffic speed prediction. Dest-ResNet is a sequence learning framework that ...
Then Dest-ResNet (Deep spatiotemporal Residual Network) is proposed for hotspot traffic speed prediction. Dest-ResNet is a sequence learning framework that ...
Dest-ResNet (Deep spatiotemporal Residual Network) is proposed for hotspot traffic speed prediction and shows a 30% relative boost over the state-of-the-art ...
Apr 27, 2024 · Then Dest-ResNet (Deep spatiotemporal Residual Network) is proposed for hotspot traffic speed prediction. Dest-ResNet is a sequence learning ...
Dest-ResNet: A Deep Spatiotemporal Residual Network for Hotspot Traffic Speed Prediction. Jingqing Zhang, Yike Gao. Imperial College London. Research output ...
Dest-ResNet: A Deep Spatiotemporal Residual Network for Hotspot Traffic Speed Prediction. B. Liao, J. Zhang, M. Cai, S. Tang, Y. Gao, C. Wu, S. Yang, W. Zhu, ...
Bibliographic details on Dest-ResNet: A Deep Spatiotemporal Residual Network for Hotspot Traffic Speed Prediction.
Dest-ResNet: A Deep Spatiotemporal Residual Network for Hotspot Traffic Speed Prediction. Binbing Liao, Jingqing Zhang, Ming Cai, Siliang Tang, YiFan Gao, ...
Dest-resnet: A deep spatiotemporal residual network for hotspot traffic speed prediction. B Liao, J Zhang, M Cai, S Tang, Y Gao, C Wu, S Yang, W Zhu, Y Guo ...