Chenhan Zhang
Orcid: 0000-0002-2352-0485
According to our database1,
Chenhan Zhang
authored at least 50 papers
between 2019 and 2025.
Collaborative distances:
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Bibliography
2025
Design and Optimization of a Five-Phase Reverse-Salient Fault-Tolerant Permanent Magnet Motor for Electric Vehicles.
IEEE Trans. Ind. Electron., July, 2025
A Collaborative Design of Fault Tolerance and Flux Intensifying Effect to Effectively Improve High Reliability of the PM Drive System.
IEEE Trans. Ind. Electron., July, 2025
Property-Preserving Hashing for ℓ<sub>1</sub>-Distance Predicates: Applications to Countering Adversarial Input Attacks.
CoRR, April, 2025
IEEE Trans. Inf. Forensics Secur., 2025
SCU: An Efficient Machine Unlearning Scheme for Deep Learning Enabled Semantic Communications.
IEEE Trans. Inf. Forensics Secur., 2025
IEEE Trans. Dependable Secur. Comput., 2025
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning.
IEEE Trans. Dependable Secur. Comput., 2025
Backdoored Sample Cleansing for Unlabeled Datasets via Bootstrapped Dual Set Purification.
IEEE Trans. Dependable Secur. Comput., 2025
MOUSSE: A Multimodality-Oriented Unified Semantic Communication System by Contrastive Learning.
Proceedings of the 2025 IEEE Wireless Communications and Networking Conference (WCNC), 2025
Proceedings of the Data Science: Foundations and Applications, 2025
Inversion Triplet - A Contrastive Backdoor Mitigation Method for Self-Supervised Vision Encoders.
Proceedings of the Data Science: Foundations and Applications, 2025
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025
2024
ACM Comput. Surv., April, 2024
Data-driven distributionally robust optimization under combined ambiguity for cracking production scheduling.
Comput. Chem. Eng., February, 2024
IEEE Trans. Multim., 2024
IEEE Trans. Inf. Forensics Secur., 2024
IEEE Trans. Inf. Forensics Secur., 2024
The Role of Class Information in Model Inversion Attacks Against Image Deep Learning Classifiers.
IEEE Trans. Dependable Secur. Comput., 2024
CoRR, 2024
2023
ACM Trans. Priv. Secur., November, 2023
Optimal scheduling of ethylene plants under uncertainty: An unsupervised learning-based data-driven strategy.
Comput. Ind. Eng., September, 2023
Toward Large-Scale Graph-Based Traffic Forecasting: A Data-Driven Network Partitioning Approach.
IEEE Internet Things J., March, 2023
Data-Driven Shape Sensing in Continuum Manipulators via Sliding Resistive Flex Sensors.
CoRR, 2023
Proceedings of the 22nd IEEE International Conference on Trust, 2023
Inferring Private Data from AI Models in Metaverse through Black-box Model Inversion Attacks.
Proceedings of the IEEE International Conference on Metaverse Computing, 2023
Construct New Graphs Using Information Bottleneck Against Property Inference Attacks.
Proceedings of the IEEE International Conference on Communications, 2023
FedMC: Federated Learning with Mode Connectivity Against Distributed Backdoor Attacks.
Proceedings of the IEEE International Conference on Communications, 2023
CP-FL: Practical Gradient Leakage Defense in Federated Learning with Compressive Privacy.
Proceedings of the IEEE Global Communications Conference, 2023
Extracting Privacy-Preserving Subgraphs in Federated Graph Learning using Information Bottleneck.
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023
2022
IEEE Trans. Big Data, 2022
Toward Crowdsourced Transportation Mode Identification: A Semisupervised Federated Learning Approach.
IEEE Internet Things J., 2022
A Communication-Efficient Federated Learning Scheme for IoT-Based Traffic Forecasting.
IEEE Internet Things J., 2022
Frontiers Comput. Sci., 2022
Proceedings of the IEEE Wireless Communications and Networking Conference, 2022
Proceedings of the AI 2021: Advances in Artificial Intelligence, 2022
2021
FASTGNN: A Topological Information Protected Federated Learning Approach for Traffic Speed Forecasting.
IEEE Trans. Ind. Informatics, 2021
Complicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel.
IEEE Trans. Comput. Soc. Syst., 2021
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021
Learn Travel Time Distribution with Graph Deep Learning and Generative Adversarial Network.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021
TSTNet: A Sequence to Sequence Transformer Network for Spatial-Temporal Traffic Prediction.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021
Proceedings of the IEEE Global Communications Conference, 2021
2020
Complicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel.
CoRR, 2020
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020
An Enhanced Motif Graph Clustering-Based Deep Learning Approach for Traffic Forecasting.
Proceedings of the IEEE Global Communications Conference, 2020
2019
Spatial-Temporal Graph Attention Networks: A Deep Learning Approach for Traffic Forecasting.
IEEE Access, 2019