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Spatial effects of video compression on classification in convolutional neural networks. (2018)
Conference Proceeding
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Spatial effects of video compression on classification in convolutional neural networks. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489370. Available from: https://doi.org/10.1109/IJCNN.2018.8489370

A collection of Computer Vision application reuse pre-learned features to analyse video frame-by-frame. Those features are classically learned by Convolutional Neural Networks (CNN) trained on high quality images. However, available video content is... Read More about Spatial effects of video compression on classification in convolutional neural networks..

New trends on digitisation of complex engineering drawings. (2018)
Journal Article
MORENO-GARCIA, C.F., ELYAN, E. and JAYNE, C. 2019. New trends on digitisation of complex engineering drawings. Neural computing and applications [online], 31(6): selected papers from the proceedings of the 18th Engineering applications of neural networks conference (EANN 2017), 25-27 August 2017, Athens, Greece, pages 1695-1712. Available from: https://doi.org/10.1007/s00521-018-3583-1

Engineering drawings are commonly used across different industries such as oil and gas, mechanical engineering and others. Digitising these drawings is becoming increasingly important. This is mainly due to the legacy of drawings and documents that m... Read More about New trends on digitisation of complex engineering drawings..

Deep learning based approaches for imitation learning. (2018)
Thesis
HUSSEIN, A. 2018. Deep learning based approaches for imitation learning. Robert Gordon University, PhD thesis.

Imitation learning refers to an agent's ability to mimic a desired behaviour by learning from observations. The field is rapidly gaining attention due to recent advances in computational and communication capabilities as well as rising demand for int... Read More about Deep learning based approaches for imitation learning..

Cognitive modelling and control of human error processes in human-computer interaction with safety critical IT systems in telehealth. (2017)
Thesis
ALWAWI, I. 2017. Cognitive modelling and control of human error processes in human-computer interaction with safety critical IT systems in telehealth. Robert Gordon University, PhD thesis.

The field of telehealth has developed rapidly in recent years. It provides medical support particularly to those who are living in remote areas and in emergency cases. Although developments in both technology and practice have been rapid, there are s... Read More about Cognitive modelling and control of human error processes in human-computer interaction with safety critical IT systems in telehealth..

Deep imitation learning for 3D navigation tasks. (2017)
Journal Article
HUSSEIN, A., ELYAN, E., GABER, M.M. and JAYNE, C. 2018. Deep imitation learning for 3D navigation tasks. Neural computing and applications [online], 29(7), pages 389-404. Available from: https://doi.org/10.1007/s00521-017-3241-z

Deep learning techniques have shown success in learning from raw high dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imita... Read More about Deep imitation learning for 3D navigation tasks..

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..

Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings. (2017)
Conference Proceeding
MORENO-GARCÍA, C.F., ELYAN, E. and JAYNE, C. 2017. Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings. In Boracchi, G., Iliadis, L., Jayne, C. and Likas, A. (eds.) Engineering applications of neural networks: proceedings of the 18th International engineering applications of neural networks (EANN 2017), 25-27 August 2017, Athens, Greece. Communications in computer and information science, 744. Cham: Springer [online], pages 87-98. Available from: https://doi.org/10.1007/978-3-319-65172-9_8

The demand for digitisation of complex engineering drawings becomes increasingly important for the industry given the pressure to improve the efficiency and time effectiveness of operational processes. There have been numerous attempts to solve this... Read More about Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings..

Deep reward shaping from demonstrations. (2017)
Conference Proceeding
HUSSEIN, A., ELYAN, E., GABER, M.M. and JAYNE, C. 2017. Deep reward shaping from demonstrations. In Proceedings of the 2017 International joint conference on neural networks (IJCNN 2017), 14-19 May 2017, Anchorage, USA. Piscataway: IEEE [online], article number 7965896, pages 510-517. Available from: https://doi.org/10.1109/IJCNN.2017.7965896

Deep reinforcement learning is rapidly gaining attention due to recent successes in a variety of problems. The combination of deep learning and reinforcement learning allows for a generic learning process that does not consider specific knowledge of... Read More about Deep reward shaping from demonstrations..

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..

On pruning and feature engineering in Random Forests. (2016)
Thesis
FAWAGREH, K. 2016. On pruning and feature engineering in Random Forests. Robert Gordon University, PhD thesis.

Random Forest (RF) is an ensemble classification technique that was developed by Leo Breiman over a decade ago. Compared with other ensemble techniques, it has proved its accuracy and superiority. Many researchers, however, believe that there is stil... Read More about On pruning and feature engineering in Random Forests..

An outlier ranking tree selection approach to extreme pruning of random forests. (2016)
Conference Proceeding
FAWAGREH, K., GABER, M.M. and ELYAN, E. 2016. An outlier ranking tree selection approach to extreme pruning of random forests. In Jayne, C. and Iliadis, L. (eds.) Engineering applications of neural networks: proceedings of the 17th International engineering applications of neural networks conference (EANN 2016), 2-5 September 2016, Aberdeen, UK. Communications in computer and information science, 629. Cham: Springer [online], pages 267-282. Available from: https://doi.org/10.1007/978-3-319-44188-7_20

Random Forest (RF) is an ensemble classification technique that was developed by Breiman over a decade ago. Compared with other ensemble techniques, it has proved its accuracy and superiority. Many researchers, however, believe that there is still ro... Read More about An outlier ranking tree selection approach to extreme pruning of random forests..

Deep active learning for autonomous navigation. (2016)
Conference Proceeding
HUSSEIN, A., GABER, M.M. and ELYAN, E. 2016. Deep active learning for autonomous navigation. In Jayne, C. and Iliadis, L. (eds.) Engineering applications of neural networks: proceedings of the 17th International engineering applications of neural networks conference (EANN 2016), 2-5 September 2016, Aberdeen, UK. Communications in computer and information science, 629. Cham: Springer [online], pages 3-17. Available from: https://doi.org/10.1007/978-3-319-44188-7_1

Imitation learning refers to an agent's ability to mimic a desired behavior by learning from observations. A major challenge facing learning from demonstrations is to represent the demonstrations in a manner that is adequate for learning and efficien... Read More about Deep active learning for autonomous navigation..

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..

3D anthropometry: quantifying the shape and size variability within the UK male offshore oil and gas workforce. (2016)
Thesis
LEDINGHAM, R.J. 2016. 3D anthropometry: quantifying the shape and size variability within the UK male offshore oil and gas workforce. Robert Gordon University, MRes thesis.

Background: UK male offshore workers typically increased in weight by 19% since 1985, and are also heavier than the background UK male population. Aim: To conduct an anthropometric survey on UK offshore workers, employing the latest portable 3D scann... Read More about 3D anthropometry: quantifying the shape and size variability within the UK male offshore oil and gas workforce..

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..

Content based video retrieval via spatial-temporal information discovery. (2013)
Thesis
WANG, L. 2013. Content based video retrieval via spatial-temporal information discovery. Robert Gordon University, PhD thesis.

Content based video retrieval (CBVR) has been strongly motivated by a variety of realworld applications. Most state-of-the-art CBVR systems are built based on Bag-of-visual- Words (BovW) framework for visual resources representation and access. The f... Read More about Content based video retrieval via spatial-temporal information discovery..

An investigation into the cognitive effects of instructional interface visualisations. (2013)
Thesis
AKINLOFA, O.R. 2013. An investigation into the cognitive effects of instructional interface visualisations. Robert Gordon University, PhD thesis.

An investigation is conducted into the cognitive effects of using different computer based instructions media in acquisition of specific novel human skills. With recent rapid advances in computing and multimedia instructional delivery, several contem... Read More about An investigation into the cognitive effects of instructional interface visualisations..

Improving bag-of-visual-words model with spatial-temporal correlation for video retrieval. (2012)
Conference Proceeding
WANG, L., SONG, D. and ELYAN, E. 2012. Improving bag-of-visual-words model with spatial-temporal correlation for video retrieval. In Proceedings of the 21st Association for Computing Machinery (ACM) international conference on information and knowledge management (CIKM'12), 29 October - 2 November 2012, Maui, USA. New York: ACM [online], pages 1303-1312. Available from: https://doi.org/10.1145/2396761.2398433

Most of the state-of-art approaches to Query-by-Example (QBE) video retrieval are based on the Bag-of-visual-Words (BovW) representation of visual content. It, however, ignores the spatial-temporal information, which is important for similarity measu... Read More about Improving bag-of-visual-words model with spatial-temporal correlation for video retrieval..