Outputs (1093)

Large kernel spectral and spatial attention networks for hyperspectral image classification. (2023)
Journal Article
SUN, G., PAN, Z., ZHANG, A., JIA, X., REN, J., FU, H. and YAN, K. 2023. Large kernel spectral and spatial attention networks for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 61, article 5519915. Available from: https://doi.org/10.1109/tgrs.2023.3292065

Currently, long-range spectral and spatial dependencies have been widely demonstrated to be essential for hyperspectral image (HSI) classification. Due to the transformer superior ability to exploit long-range representations, the transformer-based m... Read More about Large kernel spectral and spatial attention networks for hyperspectral image classification..

Managing group projects in undergraduate computing. (2023)
Presentation / Conference
SCOTT, M.J., ALSHAIGY, B., SIEGEL, A.A. and ZARB, M. 2023. Managing group projects in undergraduate computing. Panel presented at the 28th Annual conference on innovation and technology in computer science education (ITiCSE 2023), 8-12 July 2023, Turku, Finland.

This panel convenes four educators, each from different institutions and each with experience managing group projects. Their expertise spans topics including: peer assessment and peer evaluation; entrepreneurship; transdisciplinarity; internationalis... Read More about Managing group projects in undergraduate computing..

3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration. (2023)
Journal Article
ZHANG, H., MEKALA, M.S., YANG, D., ISAACS, J., NAIN, Z., PARK, J.H. and JUNG, H.-Y. 2023. 3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration. IEEE transactions on vehicular technology [online], 72(12), pages 15268-15279. Available from: https://doi.org/10.1109/TVT.2023.3291650

The use of edge computing for 3D perception has garnered interest in intelligent transportation systems (ITS) due to its potential to enhance Vehicle-to-Everything (V2X) orchestration through real-time traffic monitoring. The ability to accurately me... Read More about 3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration..

Machine learning for risk stratification of diabetic foot ulcers using biomarkers. (2023)
Conference Proceeding
MARTIN, K., UPHADYAY, A., WIJEKOON, A., WIRATUNGA, N. and MASSIE, S. [2023]. Machine learning for risk stratification of diabetic foot ulcers using biomarkers. To be presented at the 2023 International conference on computational science (ICCS 2023): computing at the cutting edge of science, 3-5 July 2023, Prague, Czech Republic: [virtual event].

Development of a Diabetic Foot Ulcer (DFU) causes a sharp decline in a patient's health and quality of life. The process of risk stratification is crucial for informing the care that a patient should receive to help manage their Diabetes before an ul... Read More about Machine learning for risk stratification of diabetic foot ulcers using biomarkers..

A system dynamics approach to evaluate advanced persistent threat vectors. (2023)
Journal Article
NICHO, M., MCDERMOTT, C.D., FAKHRY, H. and GIRIJA, S. 2023. A system dynamics approach to evaluate advanced persistent threat vectors. International journal of information security and privacy [online], 17(1), pages 1-23. Available from: https://doi.org/10.4018/IJISP.324064

Cyber-attacks targeting high-profile entities are focused, persistent, and employ common vectors with varying levels of sophistication to exploit social-technical vulnerabilities. Advanced persistent threats (APTs) deploy zero-day malware against suc... Read More about A system dynamics approach to evaluate advanced persistent threat vectors..

Exploring students' independent learning and its relationship to mindset and academic performance. (2023)
Presentation / Conference
FORBES-MCKAY, K.E., BREMNER, P. and JOHNSTON, P. 2023. Exploring students' independent learning and its relationship to mindset and academic performance. Presented at the 2023 International higher education teaching and learning annual conference (HETL 2023): re-imagining education: collaboration and compassion, 12-14 June 2023, Aberdeen, UK.

There is increasing interest in the role of independent learning (IL) in higher education (Thomas, 2015). Indeed, several studies demonstrate the impact of IL on students' academic achievement (Difrancesca et al. 2016). Research also suggests that mo... Read More about Exploring students' independent learning and its relationship to mindset and academic performance..

Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections. (2023)
Conference Proceeding
TORAL-QUIJAS, L.A., ELYAN, E., MORENO-GARCÍA, C.F. and STANDER, J. 2023. Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections. In Iliadis, L, Maglogiannis, I., Alonso, S., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 24th International conference on engineering applications of neural networks (EAAAI/EANN 2023), 14-17 June 2023, León, Spain. Communications in computer and information science, 1826. Cham: Springer [online], pages 217-226. Available from: https://doi.org/10.1007/978-3-031-34204-2_19

Inspecting circumferential welds in caissons is a critical task for ensuring the safety and reliability of structures in the offshore industry. However, identifying and classifying different types of circumferential welds can be challenging in subsea... Read More about Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections..

DEFEG: deep ensemble with weighted feature generation. (2023)
Journal Article
LUONG, A.V., NGUYEN, T.T., HAN, K., VU, T.H., MCCALL, J. and LIEW, A.W.-C. 2023. DEFEG: deep ensemble with weighted feature generation. Knowledge-based systems [online], 275, article 110691. Available from: https://doi.org/10.1016/j.knosys.2023.110691

With the significant breakthrough of Deep Neural Networks in recent years, multi-layer architecture has influenced other sub-fields of machine learning including ensemble learning. In 2017, Zhou and Feng introduced a deep random forest called gcFores... Read More about DEFEG: deep ensemble with weighted feature generation..

Towards handling temporal dependence in concept drift streams. (2023)
Thesis
WARES, S.B. 2023. Towards handling temporal dependence in concept drift streams. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2271523

Modern technological advancements have led to the production of an incomprehensible amount of data from a wide array of devices. A constant supply of new data provides an invaluable opportunity for access to qualitative and quantitative insights. Org... Read More about Towards handling temporal dependence in concept drift streams..

On the UK smart metering system and value of data for distribution system operators. (2023)
Conference Proceeding
NUMAIR, M., ABOUSHADY, A.A., FARRAG, M.E. and ELYAN, E. 2023. On the UK smart metering system and value of data for distribution system operators. In Proceedings of the 19th International conference on AC and DC power transmission 2023 (ACDC 2023), 1-3 March 2023, Glasgow, UK. IET conference proceedings, 2023(1). Stevenage: IET [online], pages 174-180. Available from: https://doi.org/10.1049/icp.2023.1326

The Smart Metering Implementation Programme (SMIP) is an ongoing energy infrastructure upgrade that is delivering 53 million smart electricity and gas meters for homes and small businesses in the UK. The programme is expected to deliver economic bene... Read More about On the UK smart metering system and value of data for distribution system operators..