All Outputs (14)

On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems. (2022)
Conference Proceeding
HAN, K., CHRISTIE, L.A., ZAVOIANU, A.-C. and MCCALL, J. 2022. On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems. In Moreno-Díaz, R., Pichler, F. and Quesada-Arencibia, A. (eds.) Computer aided systems theory: Eurocast 2022; revised selected papers from the 18th International conference on computer aided systems theory (Eurocast 2022), 20-25 February 2022, Las Palmas, Spain. Lecture notes in computer science, 13789. Cham: Springer [online], pages 104-111. Available from: https://doi.org/10.1007/978-3-031-25312-6_12

While self-driving technology is still being perfected, public transport authorities are increasingly interested in the ability to model and optimise the benefits of adding connected and autonomous vehicles (CAVs) to existing multi-modal transport sy... Read More about On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems..

Lightweight interpolation-based surrogate modelling for multi-objective continuous optimisation. (2022)
Conference Proceeding
ZAVOIANU, A.-C., LACROIX, B. and MCCALL, J. 2022. Lightweight Interpolation-based surrogate modelling for multiobjective continuous optimisation. In Moreno-Díaz, R., Pichler, F. and Quesada-Arencibia, A. (eds.) Computer aided systems theory: Eurocast 2022; revised selected papers from the 18th International conference on computer aided systems theory (Eurocast 2022), 20-25 February 2022, Las Palmas, Spain. Lecture notes in computer science, 13789. Cham: Springer [online], pages 53-60. Available from: https://doi.org/10.1007/978-3-031-25312-6_6

We propose two surrogate-based strategies for increasing the convergence speed of multi-objective evolutionary algorithms (MOEAs) by stimulating the creation of high-quality individuals early in the run. Both offspring generation strategies are desig... Read More about Lightweight interpolation-based surrogate modelling for multi-objective continuous optimisation..

Mobile Platform for livestock monitoring and inspection. (2022)
Conference Proceeding
FABIYI, S.D., REN, J., HAN, Y., ZHU, Q. and BARCLAY, D. 2022. Mobile platform for livestock monitoring and inspection. In Proceedings of the 3rd International informatics and software engineering conference 2022 (IISEC 2022), 15-16 December 2022, Ankara, Turkey. Piscataway: IEEE [online], article 9998279. Available from: https://doi.org/10.1109/iisec56263.2022.9998297

Livestock keepers acquire and manage information (e.g. identification numbers, images, etc.) about livestock to identify and keep track of livestock using systems with capabilities to extract such information. Examples of such systems are Radio Frequ... Read More about Mobile Platform for livestock monitoring and inspection..

Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation. (2022)
Conference Proceeding
DANG, T., NGUYEN, T.T., MCCALL, J. and LIEW, A.W.-C. 2022. Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation. In Ishibuchi, H., Kwoh, C.-K., Tan, A.-H., Srinivasan, D., Miao, C., Trivedi, A. and Crockett, K. (eds.) Proceedings of the 2022 IEEE Symposium series on computational intelligence (SSCI 2022), 4-7 December 2022, Singapore. Piscataway: IEEE [online], pages 269-276. Available from: https://doi.org/10.1109/SSCI51031.2022.10022114

Segmentation, a process of partitioning an image into multiple segments to locate objects and boundaries, is considered one of the most essential medical imaging process. In recent years, Deep Neural Networks (DNN) have achieved many notable successe... Read More about Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation..

Job assignment problem and traveling salesman problem: a linked optimisation problem. (2022)
Conference Proceeding
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2022. Job assignment problem and traveling salesman problem: a linked optimisation problem. In Bramer, M. and Stahl, F (eds.) Artificial intelligence XXXIX: proceedings of the 42nd SGAI (Specialist Group on Artificial Intelligence) Artificial intelligence international conference 2022 (AI 2022), 13-15 December 2022, Cambridge, UK. Lecture notes in computer science (LNCS), 13652. Cham: Springer [online], pages 19-33. Available from: https://doi.org/10.1007/978-3-031-21441-7_2

Linked decision-making in service management systems has attracted strong adoption of optimisation algorithms. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems. This paper, theref... Read More about Job assignment problem and traveling salesman problem: a linked optimisation problem..

Crowdsourced quality assessment of enhanced underwater images: a pilot study. (2022)
Conference Proceeding
LIN, H., MEN, H., YAN, Y., REN, J. and SAUPE, D. 2022. Crowdsourced quality assessment of enhanced underwater images: a pilot study. In Proceedings of 14th International conference on quality of multimedia experience 2022 (QoMEX 2022), 5-7 September 2022, Lippstadt, Germany. Piscataway: IEEE [online], article 9900904. Available from: https://doi.org/10.1109/QoMEX55416.2022.9900904

Underwater image enhancement (UIE) is essential for a high-quality underwater optical imaging system. While a number of UIE algorithms have been proposed in recent years, there is little study on image quality assessment (IQA) of enhanced underwater... Read More about Crowdsourced quality assessment of enhanced underwater images: a pilot study..

Analysing the fitness landscape rotation for combinatorial optimisation. (2022)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2022. Analysing the fitness landscape rotation for combinatorial optimisation. In Rudolph, G., Kononova, A.V., Aguirre, H., Kerschke, P., Ochoa, G. and Tušar, T. (eds.) Parallel problem solving from nature (PPSN XVII): proceedings of 17th Parallel problem solving from nature international conference 2022 (PPSN 2022), 10-14 September 2022, Dortmund, Germany. Lecture notes in computer science, 13398. Cham: Springer [online], pages 533-547. Available from: https://doi.org/10.1007/978-3-031-14714-2_37

Fitness landscape rotation has been widely used in the field of dynamic combinatorial optimisation to generate test problems with academic purposes. This method changes the mapping between solutions and objective values, but preserves the structure o... Read More about Analysing the fitness landscape rotation for combinatorial optimisation..

TransSLC: skin lesion classification in dermatoscopic images using transformers. (2022)
Conference Proceeding
SARKER, M.M.K., MORENO-GARCÍA, C.F., REN, J. and ELYAN, E. 2022. TransSLC: skin lesion classification in dermatoscopic images using transformers. In Yang, G., Aviles-Rivero, A., Roberts, M. and Schönlieb, C.-B. (eds.) Medical image understanding and analysis: proceedings of 26th Medical image understanding and analysis 2022 (MIUA 2022), 27-29 July 2022, Cambridge, UK. Lecture notes in computer sciences, 13413. Cham: Springer [online], pages 651-660. Available from: https://doi.org/10.1007/978-3-031-12053-4_48

Early diagnosis and treatment of skin cancer can reduce patients' fatality rates significantly. In the area of computer-aided diagnosis (CAD), the Convolutional Neural Network (CNN) has been widely used for image classification, segmentation, and rec... Read More about TransSLC: skin lesion classification in dermatoscopic images using transformers..

Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. (2022)
Conference Proceeding
DANG, T., LUONG, A.V., LIEW, A.W.C., MCCALL, J. and NGUYEN, T.T. 2022. Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. In 2022 IEEE (Institute of Electrical and Electronics Engineers) Congress on evolutionary computation (CEC 2022), co-located with 2022 IEEE International joint conferences on neural networks (IJCNN 2022), 2022 IEEE International conference on fuzzy systems (FUZZ-IEEE 2022), 18-23 July 2022, Padua, Italy. Piscataway: IEEE (online), article #1030. Available from: https://doi.org/10.1109/CEC55065.2022.9870389

Deep Neural Networks (DNNs) have created a breakthrough in medical image analysis in recent years. Because clinical applications of automated medical analysis are required to be reliable, robust and accurate, it is necessary to devise effective DNNs... Read More about Ensemble of deep learning models with surrogate-based optimization for medical image segmentation..

Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem. (2022)
Conference Proceeding
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2022. Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem. In Fieldsend, J. (ed.) GECCO'22 companion: proceedings of 2022 Genetic and evolutionary computation conference companion, 9-13 July 2022, Boston, USA, [virtual event]. New York: ACM [online], pages 735-738. Available from: https://doi.org/10.1145/3520304.3529033

There is a growing literature spanning several research communities that studies multiple optimisation problems whose solutions interact, thereby leading researchers to consider suitable approaches to joint solution. Real-world problems, like supply... Read More about Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem..

The intersection of evolutionary computation and explainable AI. (2022)
Conference Proceeding
BACARDIT, J., BROWNLEE, A.E.I., CAGNONI, S., IACCA, G., MCCALL, J. and WALKER, D. 2022. The intersection of evolutionary computation and explainable AI. In Fieldsend, J. (ed.) GECCO'22 companion: proceedings of 2022 Genetic and evolutionary computation conference companion, 9-13 July 2022, Boston, USA, [virtual event]. New York: ACM [online], pages 1757-1762. Available from: https://doi.org/10.1145/3520304.3533974

In the past decade, Explainable Artificial Intelligence (XAI) has attracted a great interest in the research community, motivated by the need for explanations in critical AI applications. Some recent advances in XAI are based on Evolutionary Computat... Read More about The intersection of evolutionary computation and explainable AI..

Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. (2022)
Conference Proceeding
YAN, Y., ZHANG, Y., REN, J., HADJAL, M., MCKEE, D., KAO, F.-J., and DURRANI, T. 2022. Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. In Liang, Q., Wang, W., Liu, X., Na, Z. and Zhang, B. (eds.) Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems 2021 (CSPS 2021), 21-22 August 2021, Baishishan, China. Lecture notes in electrical engineering, 878. Singapore: Springer [online], 1, pages 582-587. Available from: https://doi.org/10.1007/978-981-19-0390-8_71

Marine Scotland is tasked with reporting on the environmental status of Scottish marine waters, an enormous area of water extending from the shoreline to deep oceanic waters. As one of the most important variables, chlorophyll concentration (Chl) pla... Read More about Estimation of chlorophyll concentration for environment monitoring in Scottish marine water..

Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation. (2022)
Conference Proceeding
CHEN, S., YAN, Y., REN, J., HWANG, B., MARSHALL, S. and DARRANI, T. 2022. Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation. In Liang, Q., Wang, W., Liu, X., Na, Z. and Zhang, B. (eds.) Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems 2021 (CSPS 2021), 21-22 August 2021, Baishishan, China. Lecture notes in electrical engineering, 878. Singapore: Springer [online], 1, pages 1004-1012. Available from: https://doi.org/10.1007/978-981-19-0390-8_126

By grouping pixels with visual coherence, superpixel algorithms provide an alternative representation of regular pixel grid for precise and efficient image segmentation. In this paper, a multi-stage model is used for sea ice segmentation from the hig... Read More about Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation..

Transfer learning with 2D vibration images for fault diagnosis of bearings under variable speed. (2022)
Conference Proceeding
AHMAD, Z., HASAN, M.J. and KIM, J.-M. 2022. Transfer learning with 2D vibration images for fault diagnosis of bearings under variable speed. In Abraham, A., Gandhi, N., Hanne, T., Hong, T.-P., Rios, T.N. and Ding, W. (eds.) Intelligent systems design and applications: proceedings of 21st International conference on intelligent systems design and applications (ISDA 2021), 13-15 December 2021, [virtual event]. Lecture notes in networks and systems, 418. Cham: Springer [online], pages 154-164. Available from: https://doi.org/10.1007/978-3-030-96308-8_14

One of the most critical assignments in fault diagnosis is to decide the finest set of features by evaluating the statistical parameters of the time-domain signals. However, these parameters are vulnerable under variable speed conditions, i.e., diffe... Read More about Transfer learning with 2D vibration images for fault diagnosis of bearings under variable speed..