Results for Deep Learning

Publications & Outputs

1. FADNet: Greenhouse Identification with Fusion Attention Mechanism and Deformable Convolution

   Liu, J., Xu, X., Bilal, M. & Jiang, J., 1/04/2024, In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17, p. 7170 - 7178 8 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

2. START: Straggler Prediction and Mitigation for Cloud Computing Environments using Encoder LSTM Networks

   Tuli, S., Singh Gill, S., Garraghan, P., Buyya, R., Casale, G. & Jennings, N. R., 31/01/2023, In: IEEE Transactions on Services Computing. 16, 1, p. 615-627 13 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

3. Cross-Domain Activity Recognition Using Shared Representation in Sensor Data

   Hamad, R. A., Yang, L., Woo, W. L. & Wei, B., 1/07/2022, In: IEEE Sensors Journal. 22, 13, p. 13273-13284 12 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

4. Trimmer: Cost-Efficient Deep Learning Auto-tuning for Cloud Datacenters

   Borowiec, D., Yeung, G-F., Friday, A., Harper, R. H. R. & Garraghan, P., 11/05/2022, (Accepted/In press) IEEE International Conference on Cloud Computing. CLOUD 22. IEEE

   Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

5. An Attention-Based U-Net for Detecting Deforestation Within Satellite Sensor Imagery

   John, D. & Zhang, C., 31/03/2022, In: International Journal of Applied Earth Observation and Geoinformation. 107, 9 p., 102685.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

6. Horus: Interference-Aware and Prediction-Based Scheduling in Deep Learning Systems

   Yeung, G-F., Borowiec, D., Yang, R., Friday, A., Harper, R. H. R. & Garraghan, P., 31/01/2022, In: IEEE Transactions on Parallel and Distributed Systems. 33, 1, p. 88-100 13 p., 21015055.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

7. Advanced data-driven modelling approaches to alarm-related fault detection and condition monitoring of wind turbines

   Wu, Y., 2022, (Unpublished) Lancaster University. 202 p.

   Research output: Thesis › Doctoral Thesis

8. ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery

   Li, R., Zheng, S., Zhang, C., Duan, C., Wang, L. & Atkinson, P., 30/11/2021, In: ISPRS Journal of Photogrammetry and Remote Sensing. 181, p. 84-98 15 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

9. Horus: An Interference-aware Resource Manager for Deep Learning Systems

   Yeung, G., Borowiec, D., Yang, R., Friday, A., Harper, R. H. R. & Garraghan, P., 29/09/2020, Algorithms and Architectures for Parallel Processing. ICA3PP 2020. Qiu, M. (ed.). Springer, p. 492-508 17 p. (Lecture Notes in Computer Science; vol. 12453).

   Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

10. The Law of Armed Conflict Issues Created by Programming Automatic Target Recognition Systems Using Deep Learning Methods

    Hughes, J., 4/11/2019, Yearbook of International Humanitarian Law. Gill, T. D., Geiss, R., Krieger, H. & Paulussen, C. (eds.). The Hague: T.M.C. Asser Press, p. 99-135 37 p. (Yearbook of International Humanitarian Law; vol. 21, no. 2018).

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

11. Convolutional Neural Network based power generation prediction of wave energy converter

    Ni, C., Ma, X. & Bai, Y., 1/07/2019, Proceedings of the 24th International Conference on Automation and Computing. IEEE, p. 460-465 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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