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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..

Twitter response to televised political debates in Election 2015. (2015)
Book Chapter
PEDERSEN, S., BAXTER, G., BURNETT, S., MACLEOD, I., GOKER, A., HERON, M., ISAACS, J., ELYAN, E. and KALICIAK, L. 2015. Twitter response to televised political debates in Election 2015. In Jackson, D. and Thorsen, E. (eds.) UK election analysis 2015: media, voters and the campaign: early reflections from leading UK academics. Poole: Bournemouth University, centre for the study of journalism, culture and community [online], page 73. Available from: http://www.electionanalysis.uk/uk-election-analysis-2015/section-6-social-media/twitter-response-to-televised-political-debates-in-election-2015/

The advent of social media such as Twitter has revolutionised our conversations about live television events. In the days before the Internet, conversation about television programmes was limited to those sitting on the sofa with you and people you m... Read More about Twitter response to televised political debates in Election 2015..

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..