Alistair McEwan
| Name | Alistair McEwan |
|---|---|
| Job title | Head of Discipline of Computing |
| Research institute | College of Science and Engineering |
| ORCID | https://orcid.org/0000-0002-6660-3192 |
Research outputs
A robust feature adaptation approach against variation of muscle contraction forces for myoelectric pattern recognition-based gesture characterization
Samuel, O., Asogbon, M. and McEwan, A. 2024. A robust feature adaptation approach against variation of muscle contraction forces for myoelectric pattern recognition-based gesture characterization. Biomedical Signal Processing and Control. 95 (2024), p. 106446. https://doi.org/https://doi.org/10.1016/j.bspc.2024.106446A Multi-Dataset Characterization of Window-based Hyperparameters for Deep CNN-driven sEMG Pattern Recognition
Kulwa, F., Zhang, H., Samuel, O., Asogbon, M., Scheme, E., Kushaba, R., McEwan, A. and Li, G. 2023. A Multi-Dataset Characterization of Window-based Hyperparameters for Deep CNN-driven sEMG Pattern Recognition. IEEE Transactions on Human-Machine Systems. pp. 1-12. https://doi.org/10.1109/THMS.2023.3329536An Attention-based Bidirectional LSTM Model for Continuous Cross-subject Estimation of Knee Joint Angle during Running from sEMG Signals
Zangene, A., Samuel, O., Abbasi, A., Nazarpour, K., McEwan, A. and Li, G. 2023. An Attention-based Bidirectional LSTM Model for Continuous Cross-subject Estimation of Knee Joint Angle during Running from sEMG Signals. 45th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society. IEEE. https://doi.org/10.1109/EMBC40787.2023.10340791Enhanced Deep Transfer Learning Model based on Spatial-Temporal driven Scalograms for Precise Decoding of Motor Intent in Stroke Survivors
Samuel, O., Asogbon, M., Kulwa, F., Zangene, A., Oyemakinde, T., Igbe, T., McEwan, A., Li, Y. and Li, G. 2023. Enhanced Deep Transfer Learning Model based on Spatial-Temporal driven Scalograms for Precise Decoding of Motor Intent in Stroke Survivors. 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE. https://doi.org/10.1109/EMBC40787.2023.10340683An efficient attention-driven deep neural network approach for continuous estimation of knee joint kinematics via sEMG signals during running
Zangene, A. R., Samuel, O., Abbasi, A., McEwan, A., Asogbon, M. G., Li, G. and Nazarpour, K. 2023. An efficient attention-driven deep neural network approach for continuous estimation of knee joint kinematics via sEMG signals during running. Biomedical Signal Processing and Control. 86 (B), pp. 1-12. https://doi.org/10.1016/j.bspc.2023.105103A systematic literature review of machine learning applications for community-acquired pneumonia
Lozano-Rojas, Daniel, Free, Robert C., McEwan, Alistair A. and Woltmann, Gerrit 2021. A systematic literature review of machine learning applications for community-acquired pneumonia. in: Lecture Notes in Electrical Engineering Springer.Blessing of dimensionality at the edge and geometry of few-shot learning
Tyukin, Ivan Y., Gorban, Alexander N., McEwan, Alistair A., Meshkinfamfard, Sepehr and Tang, Lixin 2021. Blessing of dimensionality at the edge and geometry of few-shot learning. Information Sciences. 564, pp. 124-143. https://doi.org/10.1016/j.ins.2021.01.022Bringing the Blessing of Dimensionality to the Edge
Tyukin, Ivan Y., Gorban, Alexander N, McEwan, Alistair and Meshkinfamfard, Sepehr 2019. Bringing the Blessing of Dimensionality to the Edge. IEEE. https://doi.org/10.1109/iciai.2019.8850825374
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