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Results for Feature extraction

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  1. Adversarial domain-invariant generalization: a generic domain-regressive framework for bearing fault diagnosis under unseen conditions

    Chen, L., Li, Q., Shen, C., Zhu, J., Wang, D. & Xia, M., 31/03/2022, In: IEEE Transactions on Industrial Informatics. 18, 3, p. 1790-1800 11 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  2. SSA-SiamNet: Spectral-Spatial-Wise Attention-Based Siamese Network for Hyperspectral Image Change Detection

    Wang, L., Wang, L., Wang, Q. & Atkinson, P. M., 31/01/2022, In: IEEE Transactions on Geoscience and Remote Sensing. 60, 18 p., 5510018.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  3. Muti-view Mouse Social Behaviour Recognition with Deep Graphic Model

    Jiang, Z., Zhou, F., Zhao, A., Li, X., Li, L., Tao, D. & Zhou, H., 28/05/2021, In: IEEE Transactions on Image Processing. 30, 15 p., 5490-5504.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  4. Big data analytics for short and medium-term electricity load forecasting using an AI techniques ensembler

    Ayub, N., Irfan, M., Awais, M., Ali, U., Ali, T., Hamdi, M., Alghamdi, A. & Muhammad, F., 5/10/2020, In: Energies. 13, 19, 21 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  5. Towards short term electricity load forecasting using improved support vector machine and extreme learning machine

    Ahmad, W., Ayub, N., Ali, T., Irfan, M., Awais, M., Shiraz, M. & Glowacz, A., 5/06/2020, In: Energies. 13, 11, 17 p., 2907.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  6. Enhanced feature extraction method for motor fault diagnosis using low-quality vibration data from wireless sensor networks

    Shu, Q., Lu, S., Xia, M., Ding, J., Niu, J. & Liu, Y., 15/01/2020, In: Measurement Science and Technology. 31, 4, 17 p., 045016.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  7. Flexible unsupervised feature extraction for image classification

    Liu, Y., Nie, F., Gao, Q., Gao, X., Han, J. & Shao, L., 1/07/2019, In: Neural Networks. 115, p. 65-71 7 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  8. Reducing sensor complexity for monitoring wind turbine performance using principal component analysis

    Wang, Y., Ma, X. & Joyce, M. J., 11/2016, In: Renewable Energy. 97, p. 444–456 13 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  9. Vision based human activity recognition: a review

    Bux, A., Angelov, P. P. & Habib, Z., 7/09/2016, Advances in Computational Intelligence Systems: Contributions Presented at the 16th UK Workshop on Computational Intelligence, September 7–9, 2016, Lancaster, UK. Angelov, P., Gegov, A., Jayne, C. & Shen, Q. (eds.). Springer, p. 341-371 30 p. (Advances in Intelligent Systems and Computing; vol. 513).

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

  10. A novel wavelet-based method for neutron/gamma discrimination in liquid scintillators

    Yousefi, S., Lucchese, L. & Aspinall, M. D., 2008, IEEE Nuclear Science Symposium Conference Record. IEEE, p. 2387-2391 5 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

  11. A linearised pixel-swapping method for mapping rural linear land cover features from fine spatial resolution remotely sensed imagery

    Thorton, M. W., Atkinson, P. M. & Holland, D. A., 10/2007, In: Computers and Geosciences. 33, 10, p. 1261-1272 12 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

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