Jingtao Hu
Orcid: 0000-0003-0836-2973
According to our database1,
Jingtao Hu
authored at least 41 papers
between 2006 and 2025.
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Bibliography
2025
IEEE Trans. Neural Networks Learn. Syst., January, 2025
2024
New Results on Rapid Dynamical Pattern Recognition via Deterministic Learning From Sampling Sequences.
IEEE Trans. Neural Networks Learn. Syst., September, 2024
Neural Networks, January, 2024
Explicit convergence relations for a class of discrete LTV systems and its application to performance analysis of deterministic learning.
J. Frankl. Inst., 2024
2023
Integrating reinforcement learning with deterministic learning for fault diagnosis of nonlinear systems.
Neurocomputing, December, 2023
IEEE Trans. Syst. Man Cybern. Syst., October, 2023
Neural Networks, February, 2023
IEEE Trans. Geosci. Remote. Sens., 2023
IEEE Trans. Geosci. Remote. Sens., 2023
Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning.
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Abstract: MOOD 2020 - A Public Benchmark for Out-of-distribution Detection and Localization on Medical Images.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023
Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
IEEE Trans. Neural Networks Learn. Syst., 2022
MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images.
IEEE Trans. Medical Imaging, 2022
Deterministic learning from neural control for a class of sampled-data nonlinear systems.
Inf. Sci., 2022
GADMSL: Graph Anomaly Detection on Attributed Networks via Multi-scale Substructure Learning.
CoRR, 2022
Sensitivity-based dynamic performance assessment for model predictive control with Gaussian noise.
CoRR, 2022
Proceedings of the IEEE International Conference on Multimedia and Expo, 2022
2021
CoRR, 2021
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
2020
Sensors, 2020
CoRR, 2020
2019
An Efficient and Robust Unsupervised Anomaly Detection Method Using Ensemble Random Projection in Surveillance Videos.
Sensors, 2019
Consensus Multiple Kernel K-Means Clustering With Late Fusion Alignment and Matrix-Induced Regularization.
IEEE Access, 2019
Two-stage Unsupervised Video Anomaly Detection using Low-rank based Unsupervised One-class Learning with Ridge Regression.
Proceedings of the International Joint Conference on Neural Networks, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
2018
IEEE Access, 2018
An Offline Optimization and Online Table Look-Up Strategy of Two-Layer Model Predictive Control.
IEEE Access, 2018
2015
Artificial Bee Colony Algorithm Based on K-Means Clustering for Droplet Property Optimization.
Proceedings of the Intelligent Robotics and Applications - 8th International Conference, 2015
Self-adaptive Multiple Evolution Algorithms for Image Segmentation Using Multilevel Thresholding.
Proceedings of the Bio-Inspired Computing - Theories and Applications, 2015
2013
Practical Aspects of Broken Rotor Bars Detection in PWM Voltage-Source-Inverter-Fed Squirrel-Cage Induction Motors.
J. Appl. Math., 2013
2011
Proceedings of the International Conference on Electronic and Mechanical Engineering and Information Technology, 2011
2009
Proceedings of the 9th International Conference on Hybrid Intelligent Systems (HIS 2009), 2009
2008
Neural Comput. Appl., 2008
Broken Rotor Bars Fault Detection in Induction Motors Using Park's Vector Modulus and FWNN Approach.
Proceedings of the Advances in Neural Networks, 2008
Fault Monitoring and Diagnosis of Induction Machines Based on Harmonic Wavelet Transform and Wavelet Neural Network.
Proceedings of the Fourth International Conference on Natural Computation, 2008
2007
A New BP Network Based on Improved PSO Algorithm and Its Application on Fault Diagnosis of Gas Turbine.
Proceedings of the Advances in Neural Networks, 2007
2006
Rolling Bearings Fault Diagnosis Based on Adaptive Gaussian Chirplet Spectrogram and Independent Component Analysis.
Proceedings of the Advances in Natural Computation, Second International Conference, 2006