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The effect of person order on egress time: a simulation model of evacuation from a neolithic visitor attraction. (2017)
Journal Article
STEWART, A., ELYAN, E., ISAACS, J., MCEWEN, L. and WILSON, L. 2017. The effect of person order on egress time: a simulation model of evacuation from a neolithic visitor attraction. Human factors [online], 59(8), pages 1222-1232. Available from: https://doi.org/10.1177/0018720817729608

Objective: The aim of this study was to model the egress of visitors from a Neolithic visitor attraction. Background: Tourism attracts increasing numbers of elderly and mobility-impaired visitors to our built-environment heritage sites. Some such sit... Read More about The effect of person order on egress time: a simulation model of evacuation from a neolithic visitor attraction..

Imitation learning: a survey of learning methods. (2017)
Journal Article
HUSSEIN, A., GABER, M.M., ELYAN, E. and JAYNE, C. 2017. Imitation learning: a survey of learning methods. ACM computing surveys [online], 50(2), article 21. Available from: https://doi.org/10.1145/3054912

Imitation learning techniques aim to mimic human behavior in a given task. An agent (a learning machine) is trained to perform a task from demonstrations by learning a mapping between observations and actions. The idea of teaching by imitation has be... Read More about Imitation learning: a survey of learning methods..

A genetic algorithm approach to optimising random forests applied to class engineered data. (2016)
Journal Article
ELYAN, E. and GABER, M.M. 2017. A genetic algorithm approach to optimising random forests applied to class engineered data. Information sciences [online], 384, pages 220-234. Available from: https://doi.org/10.1016/j.ins.2016.08.007

In numerous applications and especially in the life science domain, examples are labelled at a higher level of granularity. For example, binary classification is dominant in many of these datasets, with the positive class denoting the existence of a... Read More about A genetic algorithm approach to optimising random forests applied to class engineered data..

A fine-grained Random Forests using class decomposition: an application to medical diagnosis. (2015)
Journal Article
ELYAN, E. and GABER, M.M. 2015. A fine-grained Random Forests using class decomposition: an application to medical diagnosis. Neural computing and applications [online], 27(8), pages 2279-2288. Available from: https://doi.org/10.1007/s00521-015-2064-z

Class decomposition describes the process of segmenting each class into a number of homogeneous subclasses. This can be naturally achieved through clustering. Utilising class decomposition can provide a number of benefits to supervised learning, espe... Read More about A fine-grained Random Forests using class decomposition: an application to medical diagnosis..

On the relationship between variational level set-based and SOM-based active contours. (2015)
Journal Article
ABDELSAMEA, M.M., GNECCO, G., GABER, M.M. and ELYAN, E. 2015. On the relationship between variational level set-based and SOM-based active contours. Computational intelligence and neuroscience [online], 2015, article ID 109029. Available from:https://doi.org/10.1155/2015/109029

Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods hav... Read More about On the relationship between variational level set-based and SOM-based active contours..