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20172023
most citedDL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction

154 citations · 296 across the 21 of their papers we have counts for

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Showing cs.LGShow all

7 papers · 1 filter

cs.LG2022

GOF-TTE: Generative Online Federated Learning Framework for Travel Time Estimation

Zhiwen Zhang, Hongjun Wang, Jiyuan Chen +3

Estimating the travel time of a path is an essential topic for intelligent transportation systems. It serves as the foundation for real-world applications, such as traffic monitori…

cs.LG2021★ 1 cited

Event-Aware Multimodal Mobility Nowcasting

Zhaonan Wang, Renhe Jiang, Hao Xue +3

As a decisive part in the success of Mobility-as-a-Service (MaaS), spatio-temporal predictive modeling for crowd movements is a challenging task particularly considering scenarios…

cs.LG2021

Differentiable Projection for Constrained Deep Learning

Dou Huang, Haoran Zhang, Xuan Song +1

Deep neural networks (DNNs) have achieved extraordinary performance in solving different tasks in various fields. However, the conventional DNN model is steadily approaching the gr…

cs.LG2021

An open GPS trajectory dataset and benchmark for travel mode detection

Jinyu Chen, Haoran Zhang, Xuan Song +1

Travel mode detection has been a hot topic in the field of GPS trajectory-related processing. Former scholars have developed many mathematical methods to improve the accuracy of de…

cs.LG2021★ 154 cited

DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction

Renhe Jiang, Du Yin, Zhaonan Wang +7

Nowadays, with the rapid development of IoT (Internet of Things) and CPS (Cyber-Physical Systems) technologies, big spatiotemporal data are being generated from mobile phones, car…

cs.LG2019★ 8 cited

VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction

Renhe Jiang, Zekun Cai, Zhaonan Wang +5

Nowadays, massive urban human mobility data are being generated from mobile phones, car navigation systems, and traffic sensors. Predicting the density and flow of the crowd or tra…

cs.LG2018★ 1 cited

Semantic Segmentation for Urban Planning Maps based on U-Net

Zhiling Guo, Hiroaki Shengoku, Guangming Wu +6

The automatic digitizing of paper maps is a significant and challenging task for both academia and industry. As an important procedure of map digitizing, the semantic segmentation…