Jianhua Zhang
Orcid: 0000-0001-8051-4746Affiliations:
- Oslo Metropolitan University, Department of Computer Science, OsloMet Artificial Intelligence Lab, Norway
- East China University of Science and Technology, School of Information Science and Engineering, Shanghai, China (2007 - 2017)
- University of Sheffield, Intelligent Systems Research Laboratory, UK (2005 - 2006)
- University of Bochum, Germany (PhD 2005)
According to our database1,
Jianhua Zhang
authored at least 32 papers
between 2013 and 2024.
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Bibliography
2024
Generic Mental Workload Measurement Using a Shared Spatial Map Network With Different EEG Channel Layouts.
IEEE Trans. Instrum. Meas., 2024
2023
Proceedings of the 3rd International Conference on Artificial Intelligence, 2023
2020
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review.
Inf. Fusion, 2020
2019
Physiological-signal-based mental workload estimation via transfer dynamical autoencoders in a deep learning framework.
Neurocomputing, 2019
Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders.
Comput. Biol. Medicine, 2019
Emotion Recognition Using Time-frequency Analysis of EEG Signals and Machine Learning<sup>*</sup>.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019
Multi-modal Recognition of Mental Workload Using Empirical Mode Decomposition and Semi-Supervised Learning.
Proceedings of the 2019 International Conference on Cyberworlds, 2019
2018
Task-generic mental fatigue recognition based on neurophysiological signals and dynamical deep extreme learning machine.
Neurocomputing, 2018
2017
Nonlinear Dynamic Classification of Momentary Mental Workload Using Physiological Features and NARX-Model-Based Least-Squares Support Vector Machines.
IEEE Trans. Hum. Mach. Syst., 2017
Pattern Classification of Instantaneous Cognitive Task-load Through GMM Clustering, Laplacian Eigenmap, and Ensemble SVMs.
IEEE ACM Trans. Comput. Biol. Bioinform., 2017
Cross-subject recognition of operator functional states via EEG and switching deep belief networks with adaptive weights.
Neurocomputing, 2017
Cross-Subject EEG Feature Selection for Emotion Recognition Using Transfer Recursive Feature Elimination.
Frontiers Neurorobotics, 2017
Cross-subject mental workload classification using kernel spectral regression and transfer learning techniques.
Cogn. Technol. Work., 2017
A deep learning scheme for mental workload classification based on restricted Boltzmann machines.
Cogn. Technol. Work., 2017
Guest editorial for special issue on modeling and analysis of human-machine systems in transportation.
Cogn. Technol. Work., 2017
Imbalanced classification of mental workload using a cost-sensitive majority weighted minority oversampling strategy.
Cogn. Technol. Work., 2017
Dynamical recursive feature elimination technique for neurophysiological signal-based emotion recognition.
Cogn. Technol. Work., 2017
Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.
Comput. Methods Programs Biomed., 2017
Recognition of emotions using multimodal physiological signals and an ensemble deep learning model.
Comput. Methods Programs Biomed., 2017
Cross-session classification of mental workload levels using EEG and an adaptive deep learning model.
Biomed. Signal Process. Control., 2017
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017
Performance Comparison of Machine Learning Algorithms for EEG-Signal-Based Emotion Recognition.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017
2016
Soft Comput., 2016
A self-organizing fuzzy neural network for identification and control of nonlinear systems.
Proceedings of the International Conference on Control, 2016
2015
Recognition of Mental Workload Levels Under Complex Human-Machine Collaboration by Using Physiological Features and Adaptive Support Vector Machines.
IEEE Trans. Hum. Mach. Syst., 2015
Proceedings of the Seventh International Conference on Advanced Computational Intelligence, 2015
2014
Identification of temporal variations in mental workload using locally-linear-embedding-based EEG feature reduction and support-vector-machine-based clustering and classification techniques.
Comput. Methods Programs Biomed., 2014
Operator functional state classification using least-square support vector machine based recursive feature elimination technique.
Comput. Methods Programs Biomed., 2014
An incremental-PID-controlled particle swarm optimization algorithm for EEG-data-based estimation of operator functional state.
Biomed. Signal Process. Control., 2014
Neural networks and AdaBoost algorithm based ensemble models for enhanced forecasting of nonlinear time series.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
An improved boosting scheme based ensemble of Fuzzy Neural Networks for nonlinear time series prediction.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
2013
An adaptive human-machine control system based on multiple fuzzy predictive models of operator functional state.
Biomed. Signal Process. Control., 2013