Professor Eyad Elyan's Outputs (37)

Digitisation of assets from the oil and gas industry: challenges and opportunities. (2019)
Presentation / Conference Contribution
MORENO-GARCIA, C.F. and ELYAN, E. 2019. Digitisation of assets from the oil and gas industry: challenges and opportunities. In Proceedings of 2019 International conference on document analysis and recognition workshops (ICDARW), 22-25 September 2019, Sydney, Australia. Piscataway: IEEE [online], 7, pages 2-5. Available from: https://doi.org/10.1109/ICDARW.2019.60122

Automated processing and analysis of legacies of printed documents across the Oil & Gas industry provide a unique opportunity and at the same time pose a significant challenge. One particular example is the case of Piping and Instrumentation Diagrams... Read More about Digitisation of assets from the oil and gas industry: challenges and opportunities..

Learning to self-manage by intelligent monitoring, prediction and intervention. (2019)
Presentation / Conference Contribution
WIRATUNGA, N., CORSAR, D., MARTIN, K., WIJEKOON, A., ELYAN, E., COOPER, K., IBRAHIM, Z., CELIKTUTAN, O., DOBSON, R.J., MCKENNA, S., MORRIS, J., WALLER, A., ABD-ALHAMMED, R., QAHWAJI, R. and CHAUDHURI, R. 2019. Learning to self-manage by intelligent monitoring, prediction and intervention. In Wiratunga, N., Coenen, F. and Sani, S. (eds.) Proceedings of the 4th International workshop on knowledge discovery in healthcare data (KDH 2019), co-located with the 28th International joint conference on artificial intelligence (IJCAI-19), 10-11 August 2019, Macao, China. CEUR workshop proceedings, 2429. Aachen: CEUR-WS [online], pages 60-67. Available from: http://ceur-ws.org/Vol-2429/paper10.pdf

Despite the growing prevalence of multimorbidities, current digital self-management approaches still prioritise single conditions. The future of out-of-hospital care requires researchers to expand their horizons; integrated assistive technologies sho... Read More about Learning to self-manage by intelligent monitoring, prediction and intervention..

Overlap-based undersampling for improving imbalanced data classification. (2018)
Presentation / Conference Contribution
VUTTIPITTAYAMONGKOL, P., ELYAN, E., PETROVSKI, A. and JAYNE, C. 2018. Overlap-based undersampling for improving imbalanced data classification. In Yin, H., Camacho, D., Novais, P. and Tallón-Ballesteros, A. (eds.) Intelligent data engineering and automated learning: proceedings of the 19th International intelligent data engineering and automated learning conference (IDEAL 2018), 21-23 November 2018, Madrid, Spain. Lecture notes in computer science, 11341. Cham: Springer [online], pages 689-697. Available from: https://doi.org/10.1007/978-3-030-03493-1_72

Classification of imbalanced data remains an important field in machine learning. Several methods have been proposed to address the class imbalance problem including data resampling, adaptive learning and cost adjusting algorithms. Data resampling me... Read More about Overlap-based undersampling for improving imbalanced data classification..

Deep imitation learning with memory for robocup soccer simulation. (2018)
Presentation / Conference Contribution
HUSSEIN, A., ELYAN, E. and JAYNE, C. 2018. Deep imitation learning with memory for robocup soccer simulation. In Pimenidis, E. and Jayne, C. (eds.) Proceedings of the 19th International conference on engineering applications of neural networks (EANN 2018), 3-5 September 2018, Bristol, UK. Communications in computer and information science, 893. Cham: Springer [online], pages 31-43. Available from: https://doi.org/10.1007/978-3-319-98204-5_3

Imitation learning is a field that is rapidly gaining attention due to its relevance to many autonomous agent applications. Providing demonstrations of effective behaviour to teach the agent is useful in real world challenges such as sparse rewards a... Read More about Deep imitation learning with memory for robocup soccer simulation..

Toward video tampering exposure: inferring compression parameters from pixels. (2018)
Presentation / Conference Contribution
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Toward video tampering exposure: inferring compression parameters from pixels. In Pimenidis, E. and Jayne, C. (eds.) Proceedings of the 19th International conference on engineering applications of neural networks (EANN 2018), 3-5 September 2018, Bristol, UK. Communications in computer and information science, 893. Cham: Springer [online], pages 44-57, Available from: https://doi.org/10.1007/978-3-319-98204-5_4

Video tampering detection remains an open problem in the field of digital media forensics. Some existing methods focus on recompression detection because any changes made to the pixels of a video will require recompression of the complete stream. Rec... Read More about Toward video tampering exposure: inferring compression parameters from pixels..

Few-shot classifier GAN. (2018)
Presentation / Conference Contribution
ALI-GOMBE, A., ELYAN, E., SAVOYE, Y. and JAYNE, C. 2018. Few-shot classifier GAN. 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 8489387. Available from: https://doi.org/10.1109/IJCNN.2018.8489387

Fine-grained image classification with a few-shot classifier is a highly challenging open problem at the core of a numerous data labeling applications. In this paper, we present Few-shot Classifier Generative Adversarial Network as an approach for fe... Read More about Few-shot classifier GAN..

Spatial effects of video compression on classification in convolutional neural networks. (2018)
Presentation / Conference Contribution
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..

Symbols classification in engineering drawings. (2018)
Presentation / Conference Contribution
ELYAN, E., MORENO GARCIA, C. and JAYNE, C. 2018. Symbols classification in engineering drawings. 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 8489087. Available from: https://doi.org/10.1109/IJCNN.2018.8489087

Technical drawings are commonly used across different industries such as Oil and Gas, construction, mechanical and other types of engineering. In recent years, the digitization of these drawings is becoming increasingly important. In this paper, we p... Read More about Symbols classification in engineering drawings..

New trends on digitisation of complex engineering drawings. (2018)
Presentation / Conference Contribution
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..

Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings. (2017)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..

An outlier ranking tree selection approach to extreme pruning of random forests. (2016)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..

Improving bag-of-visual-words model with spatial-temporal correlation for video retrieval. (2012)
Presentation / Conference Contribution
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..

Automatic features characterization from 3d facial images. (2010)
Presentation / Conference Contribution
ELYAN, E. and UGAIL, H. 2010. Automatic features characterization from 3d facial images. In Arabnia, H.R., Deligiannidis, L. and Solo, A.M.G. (eds.) Proceedings of the 14th International computer graphics and virtual reality conference (CGVR 2010), 12-15 July 2010, Las Vegas, USA. Georgia, USA: CSREA Press, pages 67-73.

This paper presents a novel and computationally fast method for automatic identification of symmetry profile from 3D facial images. The algorithm is based on the concepts of computational geometry which yield fast and accurate results. In order to de... Read More about Automatic features characterization from 3d facial images..

Automatic 3D face recognition using Fourier descriptors. (2009)
Presentation / Conference Contribution
ELYAN, E. and UGAIL, H. 2009. Automatic 3D face recognition using Fourier descriptors. In Ugail, H., Qahwaji, R.S.R, Earnshaw, R.A. and Willis, P.J. (eds.) Proceedings of the 2009 International conference on Cyberworlds (CYBERWORLDS 2009), 7-11 September 2009, Bradford, UK. Los Alamitos: IEEE Computer Society [online], article number 5279600, pages 246-252. Available from: https://doi.org/10.1109/CW.2009.48

3D face recognition is attracting more attention due to the recent development in 3D facial data acquisition techniques. It is strongly believed that 3D Face recognition systems could overcome the inherent problems of 2D face recognition such as faci... Read More about Automatic 3D face recognition using Fourier descriptors..

Interactive surface design and manipulation using PDE-method through Autodesk Maya plug-in. (2009)
Presentation / Conference Contribution
ELYAN, E. and UGAIL, H. 2009. Interactive surface design and manipulation using PDE-method through Autodesk Maya plug-in. In Ugail, H., Qahwaji, R.S.R, Earnshaw, R.A. and Willis, P.J. (eds.) Proceedings of the 2009 International conference on Cyberworlds (CYBERWORLDS 2009), 7-11 September 2009, Bradford, UK. Los Alamitos: IEEE Computer Society [online], article number 5279653, pages 119-125. Available from: https://doi.org/10.1109/CW.2009.49

This paper aims to propose a method for geometric design, modelling and shape manipulation using minimum input design parameters. Here, we address the method for the construction of 3D geometry based on the use of Elliptic Partial Differential Equati... Read More about Interactive surface design and manipulation using PDE-method through Autodesk Maya plug-in..