Yanjun Qin
Orcid: 0000-0001-5011-8697
According to our database1,
Yanjun Qin
authored at least 23 papers
between 2017 and 2024.
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Bibliography
2024
STWave$^+$+: A Multi-Scale Efficient Spectral Graph Attention Network With Long-Term Trends for Disentangled Traffic Flow Forecasting.
IEEE Trans. Knowl. Data Eng., June, 2024
2023
Impact of multiple commitments on the performance of open innovation projects: the mediating role of trusted and vigilant knowledge interaction.
J. Knowl. Manag., 2023
A Hybrid Approach for Driving Behavior Recognition: Integration of CNN and Transformer-Encoder with EEG data.
Proceedings of the 98th IEEE Vehicular Technology Conference, 2023
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023
A Text Prompt-Based Approach for Zero-Shot Corner Case Object Detection in Autonomous Driving.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023
When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023
2022
Fine-Grained Trajectory-Based Travel Time Estimation for Multi-City Scenarios Based on Deep Meta-Learning.
IEEE Trans. Intell. Transp. Syst., 2022
Learning All Dynamics: Traffic Forecasting via Locality-Aware Spatio-Temporal Joint Transformer.
IEEE Trans. Intell. Transp. Syst., 2022
An abnormal driving behavior recognition algorithm based on the temporal convolutional network and soft thresholding.
Int. J. Intell. Syst., 2022
Memory attention enhanced graph convolution long short-term memory network for traffic forecasting.
Int. J. Intell. Syst., 2022
Next Point-of-Interest Recommendation with Auto-Correlation Enhanced Multi-Modal Transformer Network.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
2021
NDGCN: Network in Network, Dilate Convolution and Graph Convolutional Networks Based Transportation Mode Recognition.
IEEE Trans. Veh. Technol., 2021
Combining Residual and LSTM Recurrent Networks for Transportation Mode Detection Using Multimodal Sensors Integrated in Smartphones.
IEEE Trans. Intell. Transp. Syst., 2021
STformer: A Noise-Aware Efficient Spatio-Temporal Transformer Architecture for Traffic Forecasting.
CoRR, 2021
CDGNet: A Cross-Time Dynamic Graph-based Deep Learning Model for Traffic Forecasting.
CoRR, 2021
CoRR, 2021
STJLA: A Multi-Context Aware Spatio-Temporal Joint Linear Attention Network for Traffic Forecasting.
CoRR, 2021
2019
Toward Transportation Mode Recognition Using Deep Convolutional and Long Short-Term Memory Recurrent Neural Networks.
IEEE Access, 2019
Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019
2018
Int. J. Distributed Sens. Networks, 2018
Detecting Transportation Modes with Low-Power-Consumption Sensors Using Recurrent Neural Network.
Proceedings of the 2018 IEEE SmartWorld, 2018
2017
Proceedings of the 5th International Conference on Enterprise Systems, 2017