Yanjun Qin

Orcid: 0000-0001-5011-8697

According to our database1, Yanjun Qin authored at least 26 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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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

Decoding Brain-Controlled Intention for UAVs and IVs Based on Lightweight Network.
IEEE Internet Things J., June, 2024

DMGSTCN: Dynamic Multigraph Spatio-Temporal Convolution Network for Traffic Forecasting.
IEEE Internet Things J., June, 2024

MMPHGCN: A Hypergraph Convolutional Network for Detection of Driver Intention on Multimodal Physiological Signals.
IEEE Signal Process. Lett., 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

Spatio-temporal hierarchical MLP network for traffic forecasting.
Inf. Sci., 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

Electroencephalogram-Based Driver Emotional State Detection with Manifold Learning.
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

DMGCRN: Dynamic Multi-Graph Convolution Recurrent Network for Traffic Forecasting.
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

Transportation recognition with the Sussex-Huawei Locomotion challenge.
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
A traffic pattern detection algorithm based on multimodal sensing.
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
Transportation Mode Recognition Algorithm Based on Bayesian Voting.
Proceedings of the 5th International Conference on Enterprise Systems, 2017


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