Kun Yang

Orcid: 0000-0002-9956-2200

Affiliations:
  • Fudan University, Academy for Engineering and Technology, Shanghai, China
  • Donghua University, Shanghai, China (2020)


According to our database1, Kun Yang authored at least 14 papers between 2022 and 2024.

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

Timeline

Legend:

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Bibliography

2024
AMP-Net: Appearance-Motion Prototype Network Assisted Automatic Video Anomaly Detection System.
IEEE Trans. Ind. Informatics, February, 2024

A novel hierarchical distributed vehicular edge computing framework for supporting intelligent driving.
Ad Hoc Networks, February, 2024

Robust Emotion Recognition in Context Debiasing.
CoRR, 2024

Towards Multimodal Sentiment Analysis Debiasing via Bias Purification.
CoRR, 2024

A Unified Self-Distillation Framework for Multimodal Sentiment Analysis with Uncertain Missing Modalities.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Target and source modality co-reinforcement for emotion understanding from asynchronous multimodal sequences.
Knowl. Based Syst., April, 2023

How2comm: Communication-Efficient and Collaboration-Pragmatic Multi-Agent Perception.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

What2comm: Towards Communication-efficient Collaborative Perception via Feature Decoupling.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

A Novel Robust Reinforcement Learning-based Dependent Task Offloading Algorithm for Mobile Edge Intelligence.
Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023

Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perception.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Novel Multi-Factor Aware Online Scheduling Method for Improving Vehicular Edge Computing Efficiency.
Proceedings of the IEEE International Conference on Communications, 2023

A Novel Efficient Multi-View Traffic-Related Object Detection Framework.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
A Novel Distributed Task Scheduling Framework for Supporting Vehicular Edge Intelligence.
Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems, 2022


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