Now showing items 1-17 of 17

  • Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening. 

    Rahim, Sarni Suhaila; Jayne, Chrisina; Palade, Vasile; Shuttleworth, James (Springer https://doi.org/10.1007/s00521-015-1929-5, 2015-06-07)
    RAHIM, S.S., JAYNE, C., PALADE, V. and SHUTTLEWORTH, J. 2016. Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening. Neural computing and applications [online], 27(5), pages 1149-1164. Available from: https://doi.org/10.1007/s00521-015-1929-5.
    Regular eye screening is essential for the early detection and treatment of the diabetic retinopathy. This paper presents a novel automatic screening system for diabetic retinopathy that focuses on the detection of the ...
  • Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing. 

    Rahim, Sarni Suhaila; Palade, Vasile; Shuttleworth, James; Jayne, Chrisina (Springer https://dx.doi.org/10.1007/s40708-016-0045-3, 2016-03-16)
    RAHIM, S.S., PALADE, V., SHUTTLEWORTH, J. and JAYNE, C. 2016. Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing. Brain informatics [online], OnlineFirst. Available from: https://dx.doi.org/10.1007/s40708-016-0045-3
    Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases ...
  • Comparative analysis of relevance feedback methods based on two user studies. 

    Akuma, Stephen; Iqbal, Rahat; Jayne, Chrisina; Doctor, Faiyaz (Elsevier http://dx.doi.org/10.1016/j.chb.2016.02.064, 2016-02-27)
    AKUMA, S., IQBAL, R., JAYNE, C. and DOCTOR, F. 2016. Comparative analysis of relevance feedback methods based on two user studies. Computers in human behavior [online], 60, pages 138-146. Available from: http://dx.doi.org/10.1016/j.chb.2016.02.064
    Rigorous analysis of user interest in web documents is essential for the development of recommender systems. This paper investigates the relationship between the implicit parameters and user explicit rating during their ...
  • Deep imitation learning for 3D navigation tasks. 

    Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina (Springer https://doi.org/10.1007/s00521-017-3241-z, 2017-12-04)
    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, ...
  • Deep imitation learning with memory for robocup soccer simulation. 

    Hussein, Ahmed; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-98204-5_3, 2018-07-27)
    HUSSEIN, A., ELYAN, E. and JAYNE, C. 2018. Deep imitation learning with memory for robocup soccer simulation. In Pimenidis, E. and Jayne, C. (eds.) Communications in computers and information science, 893: engineering applications of neural networks; proceedings of the 19th international engineering applications of neural networks (EANN 2018), 3-5 September 2018, Bristol, UK. 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 ...
  • Deep learning based approaches for imitation learning. 

    Hussein, Ahmed (Robert Gordon University School of Computing Science and Digital Media, 2018-05-01)
    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 ...
  • Deep reward shaping from demonstrations. 

    Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina (IEEE https://doi.org/10.1109/IJCNN.2017.7965896, 2017-05-14)
    HUSSEIN, A., ELYAN, E., GABER, M.M. and JAYNE, C. 2017. Deep reward shaping from demonstrations. In Proceedings of the International joint conference on neural networks (IJCNN 2017), 14 - 19 May 2017, Anchorage, USA. Piscataway, NJ: IEEE [online], 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 ...
  • An Empirical study of neural network-based audience response technology in a human anatomy course for pharmacy students. 

    Fernandez-Aleman, Jose Luis; Lopez-Gonzalez, Laura; Gonzalez-Sequeros, Ofelia; Jayne, Chrisina; Lopez-Jimenez, Juan Jose; Carrillo-de-Gea, Juan Manuel; Toval, Ambrosio (Springer http://dx.doi.org/10.1007/s10916-016-0440-6, 2016-01-27)
    FERNANDEZ-ALEMAN, J.L., LOPEZ-GONZALEZ, L., GONZALEZ-SEQUEROS, O., JAYNE, C., LOPEZ-JIMENEZ, J., CARRILLO-DE-GEA, J.M. and TOVAL, A. An empirical study of neural network-based audience response technology in a human anatomy course for pharmacy students. Journal of Medical Systems, Vol 40 (4), Article 85.
    This paper presents an empirical study of a formative neural network-based assessment approach by using mobile technology to provide pharmacy students with intelligent diagnostic feedback. An unsupervised learning algorithm ...
  • The evaluation of i-SIDRA - a tool for intelligent feedback - in a course on the anatomy of the locomotor system. 

    Fernandez-Aleman, Jose Luis; Lopez-Gonzalez, Laura; Gonzalez-Sequeros, Ofelia; Jayne, Chrisina; Lopez-Jimenez, Juan Jose; Toval, Ambrosio (Elsevier https://doi.org/10.1016/j.ijmedinf.2016.07.008, 2016-07-16)
    FERNANDEZ-ALEMAN, J.L., LOPEZ-GONZALEZ, L., GONZALEZ-SEQUEROS, O., JAYNE, C., LOPEZ-JIMENEZ, J.J. and TOVAL, A. 2016. The evaluation of i-SIDRA - a tool for intelligent feedback - in a course on the anatomy of the locomotor system. International journal of medical informatics [online], 94, pages 172-181. Available from: https://doi.org/10.1016/j.ijmedinf.2016.07.008.
    Objective: This paper presents an empirical study of a formative mobile-based assessment approach that can be used to provide students with intelligent diagnostic feedback to test its educational effectiveness. Method: An ...
  • Few-shot classifier GAN. 

    Ali-Gombe, Adamu; Elyan, Eyad; Savoye, Yann; Jayne, Chrisina (IEEE https://doi.org/10.1109/IJCNN.2018.8489387, 2018-07-08)
    ALI-GOMBE, A., ELYAN, E., SAVOYE, Y. and JAYNE, C. 2018. Few-shot classifier GAN. In Proceedings of the International joint conference on neural networks 2018 (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway: IEEE [online], article ID 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 ...
  • Imitation learning: a suvey of learning methods. 

    Hussein, Ahmed; Gaber, Mohamed Medhat; Elyan, Eyad; Jayne, Chrisina (ACM https://doi.org/10.1145/3054912, 2017-04-11)
    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 ...
  • New trends on digitisation of complex engineering drawings. 

    Moreno-García, Carlos Francisco; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/s00521-018-3583-1, 2018-06-13)
    MORENO-GARCIA, C.F., ELYAN, E. and JAYNE, C. 2018. New trends on digitisation of complex engineering drawings. Neural computing and applications [online], OnlineFirst. 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 ...
  • Overlap-based undersampling for improving imbalanced data classification. 

    Vuttipittayamongkol, Pattaramon; Elyan, Eyad; Petrovski, Andrei; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-030-03493-1_72, 2018-11-09)
    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 ...
  • Selective dropout for deep neural networks. 

    Barrow, Erik; Eastwood, Mark; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-46675-0_57, 2016-09-29)
    BARROW, E., EASTWOOD, M. and JAYNE, C. 2016. Selective dropout for deep neural networks. Lecture notes in computer science, 9949, Neural information processing: Proceedings of 23rd International conference on neural information processing (ICONIP 2016), 16-21 October 2016, Kyoto, Japan. Cham: Springer [online], pages 519-528. Available from: https://doi.org/10.1007/978-3-319-46675-0_57.
    Dropout has been proven to be an effective method for reducing overfitting in deep artificial neural networks. We present 3 new alternative methods for performing dropout on a deep neural network which improves the ...
  • Spatial effects of video compression on classification in convolutional neural networks. 

    Johnston, Pamela; Elyan, Eyad; Jayne, Chrisina (IEEE, 2018-07-08)
    JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Spatial effects of video compression on classification in convolutional neural networks. In Proceedings of the International joint conference on neural networks 2018 (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway: IEEE [online], article ID 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, ...
  • Symbols classification in engineering drawings. 

    Elyan, Eyad; Moreno-García, Carlos Francisco; Jayne, Chrisina (IEEE, 2018-07-08)
    ELYAN, E., MORENO GARCIA, C. and JAYNE, C. 2018. Symbols classification in engineering drawings. Presented at the International joint conference on neural networks 2018 (IJCNN), 8-13 July 2018, Rio de Janeiro, Brazil.
    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 ...
  • Toward video tampering exposure: inferring compression parameters from pixels. 

    Johnston, Pamela; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-98204-5_4, 2018-07-27)
    JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Toward video tampering exposure: inferring compression parameters from pixels. In Pimenidis, E. and Jayne, C. (eds.) Communications in computers and information science, 893: engineering applications of neural networks; proceedings of the 19th international engineering applications of neural networks conference (EANN 2018), 3-5 September 2018, Bristol, UK. 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 ...