Jianbo Yu
Orcid: 0000-0003-4535-7436Affiliations:
- Fudan University, Shanghai, China
According to our database1,
Jianbo Yu authored at least 20 papers
between 2020 and 2026.
Collaborative distances:
Collaborative distances:
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Bibliography
2026
Multipeeling of Homogeneous Stationarity and Heterogeneous Nonstationarity With Differentiated Learning for Process Monitoring.
IEEE Trans. Cybern., January, 2026
CoRR, January, 2026
CoRR, January, 2026
CoRR, January, 2026
EfficientFSL: Enhancing Few-Shot Classification via Query-Only Tuning in Vision Transformers.
CoRR, January, 2026
IEEE Trans. Reliab., 2026
Semantically-guided dual-branch prototypical network with dynamic margin for few-shot industrial fault diagnosis.
Neurocomputing, 2026
EfficientFSL: Enhancing Few-Shot Classification via Query-Only Tuning In Vision Transformers.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026
2025
Disentangled Feature Representation Based on Multiscale Content Learning in Industrial Heterogeneous Nonstationary Fault Detection.
IEEE Trans. Instrum. Meas., 2025
Variational Regression With Uncertainty-Variance Consistency for Semi-Supervised Sequence Soft-Sensing in Chemical Fiber Industry.
IEEE Trans. Instrum. Meas., 2025
Adaptive temporal diffusion-based reconstruction model for industrial dynamic uncertain process monitoring.
Appl. Soft Comput., 2025
2024
Semisupervised Classification With Sequence Gaussian Mixture Variational Autoencoder.
IEEE Trans. Ind. Electron., September, 2024
A Mobile Switched Attention Network for Defects Classification on Co-Fired Piezoelectric Actuators.
IEEE Trans. Instrum. Meas., 2024
Physically-guided temporal diffusion transformer for long-term time series forecasting.
Knowl. Based Syst., 2024
Mutual stacked autoencoder for unsupervised fault detection under complex multi-residual correlations.
Adv. Eng. Informatics, 2024
2022
Data-feature-driven nonlinear process monitoring based on joint deep learning models with dual-scale.
Inf. Sci., 2022
2020
Whole Process Monitoring Based on Unstable Neuron Output Information in Hidden Layers of Deep Belief Network.
IEEE Trans. Cybern., 2020
Multiscale intelligent fault detection system based on agglomerative hierarchical clustering using stacked denoising autoencoder with temporal information.
Appl. Soft Comput., 2020
Modeling Large-Scale Industrial Processes by Multiple Deep Belief Networks With Lower-Pressure and Higher-Precision for Status Monitoring.
IEEE Access, 2020