All Outputs (3)

A novel ensemble aggregation method based on deep learning representation. (2024)
Presentation / Conference Contribution
NGUYEN, T.T., ELYAN, E., DANG, T., NGUYEN, T.T. and LONGMUIR, M. 2025. A novel ensemble aggregation method based on deep learning representation. In Antonacopoulos, A., Chaudhuri, S., Chellappa, R., et al. (eds.) Pattern recognition: proceedings of the 27th International conference on pattern recognition, 01-05 December 2024, Kolkata, India. Lecture notes in computer science, 15324. Cham: Springer [online], pages 31-46. Available from: https://doi.org/10.1007/978-3-031-78383-8_3

We propose a novel ensemble aggregation method by using a deep learning-based representation approach. Specifically, we applied the Cross-Validation procedure on training data with a number of learning algorithms to obtain the predictions for trainin... Read More about A novel ensemble aggregation method based on deep learning representation..

A multiclass imbalanced dataset classification of symbols from piping and instrumentation diagrams. (2024)
Presentation / Conference Contribution
JAMIESON, L., MORENO-GARCÍA, C.F. and ELYAN, E. 2024. A multiclass imbalanced dataset classification of symbols from piping and instrumentation diagrams. In Barney Smith, E.H., Liwicki, M. and Peng, L. (eds.) Proceedings of the 18th International conference on Document analysis and recognition 2024 (ICDAR 2024), 30 August - 04 September 2024, Athens, Greece. Lecture notes in computer science, 14804. Cham: Springer [online], part 1, pages 3-16. Available from: https://doi.org/10.1007/978-3-031-70533-5_1

Engineering diagrams provide rich source of information and are widely used across different industries. Recent years have seen growing research interest in developing solutions for processing and analysing these diagrams using wide range of image-pr... Read More about A multiclass imbalanced dataset classification of symbols from piping and instrumentation diagrams..

Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies. (2024)
Presentation / Conference Contribution
HASAN, M.J., ELYAN, E., YAN, Y., REN, J. and SARKER, M.M.K. 2024. Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 220-228. Available from: https://doi.org/10.1007/978-981-97-1417-9_21

Retrofitting and thermographic survey (TS) companies in Scotland collaborate with social housing providers to tackle fuel poverty. They employ ground-level infrared (IR) camera-based-TSs (GIRTSs) for collecting thermal images to identify the heat los... Read More about Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies..