Yu Qiao

Orcid: 0000-0003-4045-8473

Affiliations:

Kyung Hee University, School of Computing, Department of Artificial Intelligence, Yongin, South Korea
Nanjing University of Information Science and Technology, School of Computer and Software, China

According to our database¹, Yu Qiao authored at least 38 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Article

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Bibliography

2024

Holographic MIMO With Integrated Sensing and Communication for Energy-Efficient Cell-Free 6G Networks.

[BibT_eX]

[DOI]

IEEE Internet Things J., October, 2024

Integrated Sensing, Localization, and Communication in Holographic MIMO-Enabled Wireless Network: A Deep Learning Approach.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Serv. Manag., February, 2024

MP-FedCL: Multiprototype Federated Contrastive Learning for Edge Intelligence.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2024

Boosting Federated Domain Generalization: Understanding the Role of Advanced Pre-Trained Architectures.

[BibT_eX]

[DOI]

CoRR, 2024

A Complete Survey on LLM-based AI Chatbots.

[BibT_eX]

[DOI]

CoRR, 2024

FedCCL: Federated Dual-Clustered Feature Contrast Under Domain Heterogeneity.

[BibT_eX]

[DOI]

CoRR, 2024

Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data.

[BibT_eX]

[DOI]

CoRR, 2024

Cross-Modal Prototype based Multimodal Federated Learning under Severely Missing Modality.

[BibT_eX]

[DOI]

CoRR, 2024

Corrections to "Attention to Monkeypox: An Interpretable Monkeypox Detection Technique Using Attention Mechanism".

[BibT_eX]

[DOI]

Sheikh Mohammed Shariful Islam

IEEE Access, 2024

Attention to Monkeypox: An Interpretable Monkeypox Detection Technique Using Attention Mechanism.

[BibT_eX]

[DOI]

Sheikh Mohammed Shariful Islam

IEEE Access, 2024

Transfer Learning Empowered Power Allocation in Holographic MIMO-enabled Wireless Network.

[BibT_eX]

[DOI]

Proceedings of the NOMS 2024 IEEE Network Operations and Management Symposium, 2024

Towards Robust Federated Learning via Logits Calibration on Non-IID Data.

[BibT_eX]

[DOI]

Proceedings of the NOMS 2024 IEEE Network Operations and Management Symposium, 2024

A Power Allocation Framework for Holographic MIMO-Aided Energy-Efficient Cell-Free Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2024

Knowledge Distillation Assisted Robust Federated Learning: Towards Edge Intelligence.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2024

2023

Understanding Segment Anything Model: SAM is Biased Towards Texture Rather than Shape.

[BibT_eX]

[DOI]

CoRR, 2023

Generative AI-driven Semantic Communication Framework for NextG Wireless Network.

[BibT_eX]

[DOI]

CoRR, 2023

FedMEKT: Distillation-based Embedding Knowledge Transfer for Multimodal Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Boosting Federated Learning Convergence with Prototype Regularization.

[BibT_eX]

[DOI]

Yu Qiao

Huy Q. Le

Choong Seon Hong

CoRR, 2023

Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

[BibT_eX]

[DOI]

CoRR, 2023

Robustness of SAM: Segment Anything Under Corruptions and Beyond.

[BibT_eX]

[DOI]

CoRR, 2023

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering.

[BibT_eX]

[DOI]

CoRR, 2023

Segment Anything Model (SAM) Meets Glass: Mirror and Transparent Objects Cannot Be Easily Detected.

[BibT_eX]

[DOI]

CoRR, 2023

One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era.

[BibT_eX]

[DOI]

CoRR, 2023

MP-FedCL: Multi-Prototype Federated Contrastive Learning for Edge Intelligence.

[BibT_eX]

[DOI]

CoRR, 2023

Prototype Helps Federated Learning: Towards Faster Convergence.

[BibT_eX]

[DOI]

CoRR, 2023

A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?

[BibT_eX]

[DOI]

CoRR, 2023

CDFed: Contribution-based Dynamic Federated Learning for Managing System and Statistical Heterogeneity.

[BibT_eX]

[DOI]

Proceedings of the NOMS 2023, 2023

Artificial Intelligence Framework for Target Oriented Integrated Sensing and Communication in Holographic MIMO.

[BibT_eX]

[DOI]

Proceedings of the NOMS 2023, 2023

An Artificial Intelligent-Driven Semantic Communication Framework for Connected Autonomous Vehicular Network.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Information Networking, 2023

A Framework for Multi-Prototype Based Federated Learning: Towards the Edge Intelligence.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Information Networking, 2023

An Artificial Intelligence Framework for Holographic Beamforming: Coexistence of Holographic MIMO and Intelligent Omni-Surface.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Information Networking, 2023

Segment Anything Model Aided Beam Prediction for the Millimeter Wave Communication.

[BibT_eX]

[DOI]

Proceedings of the 24st Asia-Pacific Network Operations and Management Symposium, 2023

Knowledge Distillation in Federated Learning: Where and How to Distill?

[BibT_eX]

[DOI]

Proceedings of the 24st Asia-Pacific Network Operations and Management Symposium, 2023

Federated Multimodal Learning for IoT Applications: A Contrastive Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the 24st Asia-Pacific Network Operations and Management Symposium, 2023

Transformer-based Communication Resource Allocation for Holographic Beamforming: A Distributed Artificial Intelligence Framework.

[BibT_eX]

[DOI]

Proceedings of the 24st Asia-Pacific Network Operations and Management Symposium, 2023

2020

A novel node selection scheme for energy-efficient cooperative spectrum sensing using D-S theory.

[BibT_eX]

[DOI]

Zilong Jin

Yu Qiao

Wirel. Networks, 2020

2018

EESS: An Energy-Efficient Spectrum Sensing Method by Optimizing Spectrum Sensing Node in Cognitive Radio Sensor Networks.

[BibT_eX]

[DOI]

Wirel. Commun. Mob. Comput., 2018

An Energy-Efficient Cooperative Spectrum Sensing Scheme based on D-S Theory in Cognitive Radio Sensor Networks.

[BibT_eX]

[DOI]

Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication, 2018

Yu Qiao

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