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Outputs (3022)

Racial Bias within Face Recognition: A Survey (2024)
Journal Article
Yucer, S., Tekras, F., Al Moubayed, N., & Breckon, T. P. (2025). Racial Bias within Face Recognition: A Survey. ACM Computing Surveys, 57(4), 1-39. https://doi.org/10.1145/3705295

Facial recognition is one of the most academically studied and industrially developed areas within computer vision where we readily find associated applications deployed globally. This widespread adoption has uncovered significant performance variati... Read More about Racial Bias within Face Recognition: A Survey.

Delving into female breast cancer: Distinct disease-specific survival outcomes between invasive lobular and ductal carcinomas revealed by propensity score matching (2024)
Journal Article
Zhang, W., Huang, Y., Zhou, Y., Xue, J., Gao, S., Kang, L., Shi, J., Zhou, T., Duan, Y., Guo, S., & Li, Q. (2024). Delving into female breast cancer: Distinct disease-specific survival outcomes between invasive lobular and ductal carcinomas revealed by propensity score matching. PLoS ONE, 19(12), Article e0300116. https://doi.org/10.1371/journal.pone.0300116

Purpose: The difference in prognosis between invasive lobular carcinoma (ILC) and invasive ductal carcinoma (IDC) is still controversial in the academic community. Resolving this controversy can help to more accurately determine patients’ prognosis,... Read More about Delving into female breast cancer: Distinct disease-specific survival outcomes between invasive lobular and ductal carcinomas revealed by propensity score matching.

Analysis of the Impact of Knowledge on Sustainable Travel Choices: an Empirical Study with Informational Videos and Gamified Quizzes (2024)
Journal Article
Murad, S., & Law, E. L.-C. (online). Analysis of the Impact of Knowledge on Sustainable Travel Choices: an Empirical Study with Informational Videos and Gamified Quizzes. Interacting with Computers, https://doi.org/10.1093/iwc/iwae056

Carbon emissions from transport are increasing on a global scale with transport accounting for the largest portion. While there is greater awareness of climate change, few people are willing to change their travel habits. To gain a better understandi... Read More about Analysis of the Impact of Knowledge on Sustainable Travel Choices: an Empirical Study with Informational Videos and Gamified Quizzes.

Artificial intelligence for geometry-based feature extraction, analysis and synthesis in artistic images: a survey (2024)
Journal Article
Vijendran, M., Deng, J., Chen, S., Ho, E. S. L., & Shum, H. P. H. (2025). Artificial intelligence for geometry-based feature extraction, analysis and synthesis in artistic images: a survey. Artificial Intelligence Review, 58(2), Article 64. https://doi.org/10.1007/s10462-024-11051-3

Artificial Intelligence significantly enhances the visual art industry by analyzing, identifying and generating digitized artistic images. This review highlights the substantial benefits of integrating geometric data into AI models, addressing challe... Read More about Artificial intelligence for geometry-based feature extraction, analysis and synthesis in artistic images: a survey.

Robust least squares twin bounded support vector machine with a generalized correntropy-induced metric (2024)
Journal Article
Yuan, C., Zhou, C., Pan, H., Arvin, F., Peng, J., & Li, H. (2025). Robust least squares twin bounded support vector machine with a generalized correntropy-induced metric. Information Sciences, 699, Article 121798. https://doi.org/10.1016/j.ins.2024.121798

The least squares twin support vector machine (LSTSVM), which aims to seek nonparallel hyperplanes by solving two linear equations, has received extensive attention in statistical theory as a powerful and widely used method for addressing classificat... Read More about Robust least squares twin bounded support vector machine with a generalized correntropy-induced metric.

Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind (2024)
Presentation / Conference Contribution
Nisi, V., Bala, P., Pessoa, M., James, S., & Nunes, N. (2024, December). Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind. Presented at International Conference on Interactive Digital Storytelling (ICIDS 2024), Barranquilla, Colombia

Due to a recent increase in conflicts, natural disasters, and economic crises, a growing wave of migrant populations has been searching for asylum in Europe. For this population of asylum seekers, the migration process, like currents and rapids, can... Read More about Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind.

Payment Scheduling in the Interval Debt Model (2024)
Journal Article
Stewart, I., Kutner, D., Friedetzky, T., Trehan, A., & Mertzios, G. (2025). Payment Scheduling in the Interval Debt Model. Theoretical Computer Science, 1028, Article 115028. https://doi.org/10.1016/j.tcs.2024.115028

The network-based study of financial systems has received considerable attention in recent years but has seldom explicitly incorporated the dynamic aspects of such systems. We consider this problem setting from the temporal point of view and introduc... Read More about Payment Scheduling in the Interval Debt Model.

Predicting effective quenching of stable pulses in slow-fast excitable media (2024)
Journal Article
Marcotte, C. D. (2024). Predicting effective quenching of stable pulses in slow-fast excitable media. Physical Review E, 110(6), Article 064210. https://doi.org/10.1103/physreve.110.064210

We develop a linear theory for the prediction of excitation wave quenching—the construction of minimal perturbations which return stable excitations to quiescence—for localized pulse solutions in models of excitable media. The theory accounts for an... Read More about Predicting effective quenching of stable pulses in slow-fast excitable media.

Beyond Syntax: How Do LLMs Understand Code? (2024)
Presentation / Conference Contribution
North, M., Atapour-Abarghouei, A., & Bencomo, N. (2025, April). Beyond Syntax: How Do LLMs Understand Code?. Presented at 2025 IEEE/ACM International Conference on Software Engineering ICSE, Ottawa , Canada

Within software engineering research, Large Language Models (LLMs) are often treated as 'black boxes', with only their inputs and outputs being considered. In this paper, we take a machine interpretability approach to examine how LLMs internally repr... Read More about Beyond Syntax: How Do LLMs Understand Code?.