Outputs (1093)

Steps towards a philosophy of computing education. (2024)
Conference Proceeding
MCDERMOTT, R., DANIELS, M. and FREZZA, S.T. 2024. Steps towards a philosophy of computer education. In Mühling, A. and Jormanainen, I. (eds.) Proceedings of the 23rd Koli calling international conference on computing education research 2023, 13-18 November 2024, Koli, Finland. New York: ACM [online], article 20. Available from: https://doi.org/10.1145/3631802.3631817

Is it meaningful to talk about the philosophy of computing education? What is its subject matter and methods? Is it different from, or a subfield of, the philosophy of science education or the philosophy of technology education or the philosophy of e... Read More about Steps towards a philosophy of computing education..

Two-layer ensemble of deep learning models for medical image segmentation. (2024)
Journal Article
DANG, T., NGUYEN, T.T., MCCALL, J., ELYAN, E. and MORENO-GARCÍA, C.F. 2024. Two-layer ensemble of deep learning models for medical image segmentation. Cognitive computation [online], In Press. Available from: https://doi.org/10.1007/s12559-024-10257-5

One of the most important areas in medical image analysis is segmentation, in which raw image data is partitioned into structured and meaningful regions to gain further insights. By using Deep Neural Networks (DNN), AI-based automated segmentation al... Read More about Two-layer ensemble of deep learning models for medical image segmentation..

Detection-driven exposure-correction network for nighttime drone-view object detection. (2024)
Journal Article
XI, Y., JIA, W., MIAO, Q., FENG, J., REN, J. and LUO, H. 2024. Detection-driven exposure-correction network for nighttime drone-view object detection. IEEE transactions on geoscience and remote sensing [online], 62, article number 5605014. Available from: https://doi.org/10.1109/TGRS.2024.3351134

Drone-view object detection (DroneDet) models typically suffer a significant performance drop when applied to nighttime scenes. Existing solutions attempt to employ an exposure-adjustment module to reveal objects hidden in dark regions before detecti... Read More about Detection-driven exposure-correction network for nighttime drone-view object detection..

Feature aggregation and region-aware learning for detection of splicing forgery. (2024)
Journal Article
XU, Y., ZHENG, J., REN, J. and FANG, A. 2024. Feature aggregation and region-aware learning for detection of splicing forgery. IEEE signal processing letters [online], 31, pages 696-700. Available from: https://doi.org/10.1109/LSP.2023.3348689

Detection of image splicing forgery become an increasingly difficult task due to the scale variations of the forged areas and the covered traces of manipulation from post-processing techniques. Most existing methods fail to jointly multi-scale local... Read More about Feature aggregation and region-aware learning for detection of splicing forgery..

In search of a philosophy of computing education. (2023)
Conference Proceeding
MCDERMOTT, R., DANIELS,M. and FREZZA, S. 2023. In search of a philosophy of computing eduction. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343513. Available from: https://doi.org/10.1109/FIE58773.2023.10343513

In this paper, we present a preliminary description of the field of inquiry encompassed by the philosophy of computing education. We first attempt to identify a general framework for investigating characteristic questions of a philosophical nature th... Read More about In search of a philosophy of computing education..

Evaluating a pass/fail grading model in first year undergraduate computing. (2023)
Conference Proceeding
ZARB, M., MCDERMOTT, R., MARTIN, K., YOUNG, T. and MCGOWAN, J. 2023. Evaluating a pass/fail grading model in first year undergraduate computing. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343276. Available from: https://doi.org/10.1109/FIE58773.2023.10343276

This Innovative Practice Full Paper investigates the implications of implementing a Pass/Fail marking scheme within the undergraduate curriculum, specifically across first year computing modules in a Scottish Higher Education Institution. The motivat... Read More about Evaluating a pass/fail grading model in first year undergraduate computing..

What is Skill? (and why does it matter?). (2023)
Conference Proceeding
MCDERMOTT, R. and DANIELS, M. 2023. What is skill? (and why does it matter?). In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343520. Available from: https://doi.org/10.1109/FIE58773.2023.10343520

This Research-to-Practice Full Paper seeks to investigate the concept of Skill within a Competency Framework, such as that described by the CC2020 document. The notion of skill is fundamental to modern educational discourse. As educators, we strive,... Read More about What is Skill? (and why does it matter?)..

Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis and prevention. (2023)
Journal Article
ALI, H., SHAH, Z., ALAM, T., WIJAYATUNGA, P. and ELYAN, E. 2023. Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis and prevention. Frontiers in radiology [online], 3, article number 1349830. Available from: https://doi.org/10.3389/fradi.2023.1349830

Artificial Intelligence (AI) has gained huge attention in computer-aided decision-making in the healthcare domain. Many novel AI methods have been developed for disease diagnosis and prognosis which may support in the prevention of disease. Most dise... Read More about Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis and prevention..

A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs. (2023)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2023. A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs. In Chova, L.G., Martínez. C.G. and Lees, J. (eds.) Proceedings of the 17th International technology, education and development conference (INTED 2023), 6-8 March 2023, Valencia, Spain. Valencia: IATED [online], pages 3261-3269. Available from: https://doi.org/10.21125/inted.2023.0897

This article describes a study in which the Learning by Developing (LbD) action model has been used as a teaching and learning method for computing students in Finland and the United Kingdom. The study has been carried out as action research, and the... Read More about A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs..

On the role of dialogue models in the age of large language models. (2023)
Conference Proceeding
WELLS, S. and SNAITH, M. 2023. On the role of dialogue models in the age of large language models. In Grasso, F., Green, N.L., Schneider, J. and Wells, S. (eds.) Proceedings of the 23rd Workshop on computational models of natural argument (CMNA 2023), 3 December 2023, [virtual event]. CEUR workshop proceedings, 3614. Aachen: CEUR-WS [online], pages 49-51. Available from: https://ceur-ws.org/Vol-3614/abstract2.pdf

We argue that Machine learning, in particular the currently prevalent generation of Large Language Models (LLMs), can work constructively with existing normative models of dialogue as exemplified by dialogue games, specifically their computational ap... Read More about On the role of dialogue models in the age of large language models..