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All Outputs (205)

Fast blur detection and parametric deconvolution of retinal fundus images (2017)
Presentation / Conference Contribution
Williams, B. M., Al-Bander, B., Pratt, H., Lawman, S., Zhao, Y., Zheng, Y., & Shen, Y. (2017, September). Fast blur detection and parametric deconvolution of retinal fundus images. Presented at International Workshop, FIFI 2017, and 4th International Workshop, OMIA 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada

Blur is a significant problem in medical imaging which can hinder diagnosis and prevent further automated or manual processing. The problem of restoring an image from blur degradation remains a challenging task in image processing. Semi-blind deblurr... Read More about Fast blur detection and parametric deconvolution of retinal fundus images.

Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer (2017)
Presentation / Conference Contribution
Butcher, J. B., Rutter, A. V., Wootton, A. J., Day, C. R., & Sulé-Suso, J. (2017, September). Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. Presented at 17th Annual UK Workshop on Computational Intelligence, Cardiff, Wales, UK

Lung cancer is a widespread disease and it is well understood that systematic, non-invasive and early detection of this progressive and life-threatening disorder is of vital importance for patient outcomes. In this work we present a convergence of fa... Read More about Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer.

An empirical approach for automatic face clustering on personal lifelogging images (2017)
Presentation / Conference Contribution
Subbaraju, V., Xu, Q., Mandal, B., Li, L., & Lim, J.-H. (2017, August). An empirical approach for automatic face clustering on personal lifelogging images. Presented at 2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP), Singapore

Life-logging applications generate a vast amount of personalized data that provides vital insights into the user's daily life. One such key insight is the people whom the user has come across/interacted with during regular life. This can be obtained... Read More about An empirical approach for automatic face clustering on personal lifelogging images.

Towards Accurate Predictions of Customer Purchasing Patterns (2017)
Presentation / Conference Contribution
Valero-Fernandez, R., Collins, D. J., Lam, K., Rigby, C., & Bailey, J. (2017, August). Towards Accurate Predictions of Customer Purchasing Patterns. Presented at 2017 IEEE International Conference on Computer and Information Technology (CIT), Helsinki, Finland

A range of algorithms was used to classify online retail customers of a UK company using historical transaction data. The predictive capabilities of the classifiers were assessed using linear regression, Lasso and regression trees. Unlike most relate... Read More about Towards Accurate Predictions of Customer Purchasing Patterns.

Towards Accurate Predictions of Customer Purchasing Patterns (2017)
Presentation / Conference Contribution
Valero-Fernandez, R., Collins, D. J., Lam, K., Rigby, C., & Bailey, J. (2017, August). Towards Accurate Predictions of Customer Purchasing Patterns. Presented at IEEE Computer and Information Technology 2017, Helsinki

range of algorithms was used to classify online retail customers of a UK company using historical transaction data. The predictive capabilities of the classifiers were assessed using linear regression, Lasso and regression trees. Unlike most related... Read More about Towards Accurate Predictions of Customer Purchasing Patterns.

A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods (2017)
Presentation / Conference Contribution
Al-Said Ahmad, A., Brereton, O., & Andras, P. (2017, July). A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods

Context: Software has become more complicated, dynamic, and asynchronous than ever, making testing more challenging. With the increasing interest in the development of cloud computing, and increasing demand for cloud-based services, it has become ess... Read More about A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods.

Learning cognitive manifolds of faces (2017)
Presentation / Conference Contribution
Li, L., Mandal, B., Tan, C., & Lim, J.-H. (2017, August). Learning cognitive manifolds of faces. Presented at 2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP), Singapore

Inspired by the studies in psychology and neuroscience, we propose a computational model of cognitive face representation that mimics the mechanism of human face perception. We propose to learn two separate manifolds for facial identity and facial ex... Read More about Learning cognitive manifolds of faces.

A Virtual 3D Cuneiform Tablet Reconstruction Interaction (2017)
Presentation / Conference Contribution
Hanes, L., Lewis, A., Nash, D., Gehlken, E., Hernandez-Munoz, L., Ch’ng, E., Woolley, S. I., & Collins, T. (2018, July). A Virtual 3D Cuneiform Tablet Reconstruction Interaction. Presented at 32nd Human Computer Interaction Conference, Belfast, Northern Ireland

Novel similarity measure for interval-valued data based on overlapping ratio (2017)
Presentation / Conference Contribution
Kabir, S., Wagner, C., Havens, T. C., Anderson, D. T., & Aickelin, U. (2017, July). Novel similarity measure for interval-valued data based on overlapping ratio. Presented at 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Naples, Italy

In computing the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal similarities for substantially different pairs... Read More about Novel similarity measure for interval-valued data based on overlapping ratio.

Searching the Past in the Future ? Joining Cuneiform Tablet Fragments in Virtual Collections (2017)
Presentation / Conference Contribution
Gehlken, E., Collins, T., Woolley, S. I., & Ch’ng, E. (2017, July). Searching the Past in the Future ? Joining Cuneiform Tablet Fragments in Virtual Collections. Paper presented at 63rd Rencontre Assyriologique Internationale, Philipps-Universität Marburg, Germany

Joining cuneiform tablet fragments are separated within and between collections worldwide. In previous work of the Virtual Cuneiform Tablet Reconstruction Project [VCTR, 2018], automated joins were achieved for virtual 3D Ur and Uruk fragments held w... Read More about Searching the Past in the Future ? Joining Cuneiform Tablet Fragments in Virtual Collections.

A Collaborative Artefact Reconstruction Environment (2017)
Presentation / Conference Contribution
Woolley, S. I., Ch’ng, E., Hernandez-Munoz, L., Gehlken, E., Collins, T., Nash, D., Lewis, A., & Hanes, L. (2017, July). A Collaborative Artefact Reconstruction Environment. Presented at 31st International BCS Human Computer Interaction Conference (HCI)

A novel collaborative artefact reconstruction environment design is presented that is informed by experimental task observation and participatory design. The motivation for the design was to enable collaborative human and computer effort in the recon... Read More about A Collaborative Artefact Reconstruction Environment.

Computer aided diagnosis of age-related macular degeneration in 3D OCT images by deep learning (2017)
Presentation / Conference Contribution
Zheng, Y., Williams, B. M., Pratt, H., Al-Bander, B., Wu, X., & Zhao, Y. (2017, May). Computer aided diagnosis of age-related macular degeneration in 3D OCT images by deep learning

Purpose : Three-dimensional (3D) optical coherence tomography (OCT) images are increasingly used in the management of eye disease, yet there has been no corresponding increase in the availability of software tools to support the analysis of large amo... Read More about Computer aided diagnosis of age-related macular degeneration in 3D OCT images by deep learning.

Automatic Feature Learning Method for Detection of Retinal Landmarks (2017)
Presentation / Conference Contribution
Al-Bander, B., Al-Nuaimy, W., Al-Taee, M. A., Al-Ataby, A., & Zheng, Y. (2016, August). Automatic Feature Learning Method for Detection of Retinal Landmarks. Presented at 2016 9th International Conference on Developments in eSystems Engineering (DeSE), Liverpool, United Kingdom

This paper presents an automatic deep learning method for location detection of important retinal landmarks, the fovea and optic disc (OD) in digital fundus retinal images with the potential for use in an automated screening and grading system. The p... Read More about Automatic Feature Learning Method for Detection of Retinal Landmarks.

Visual Augmentation Glasses for People with Impaired Vision (2017)
Presentation / Conference Contribution
Al-Ataby, A., Younis, O., Al-Nuaimy, W., Al-Taee, M., Sharaf, Z., & Al-Bander, B. (2016, August). Visual Augmentation Glasses for People with Impaired Vision. Presented at 2016 9th International Conference on Developments in eSystems Engineering (DeSE), Liverpool, United Kingdom

This paper presents the preliminary design and development of a set visual augmentation glasses with the potential to assist people with varying degrees of loss of vision. The wearable spectacles are intended to be non-obstructive, and therefore empl... Read More about Visual Augmentation Glasses for People with Impaired Vision.

Stable Clustering for Ad-Hoc Vehicle Networking (2017)
Presentation / Conference Contribution
Rossi, G., Fan, Z., Chin, W., & Leung, K. (2017, March). Stable Clustering for Ad-Hoc Vehicle Networking. Presented at IEEE Wireless Communications and Networking Conference, San Francisco, CA, USA

Vehicular ad-hoc networks (VANETs) that enable communication among vehicles and between vehicles and un- manned aerial vehicles (UAVs) and cellular base stations have re- cently attracted significant interest from the research community, due to the w... Read More about Stable Clustering for Ad-Hoc Vehicle Networking.

The Quantified Outpatient - Challenges and Opportunities in 24hr Patient Monitoring (2017)
Presentation / Conference Contribution
INFANTE SANCHEZ, D., WOOLLEY, S., COLLINS, T., PEMBERTON, P., VEENITH, T., HUME, D., LAVER, K., & SMALL, C. (2017, April). The Quantified Outpatient - Challenges and Opportunities in 24hr Patient Monitoring. Poster presented at Informatics for Health 2017, Manchester

1. Introduction Patient monitoring systems capable of accurate recording in the real-world, during the activities of everyday living, can provide rich objective accounts of patient well-being that have broad application in clinical decision support.... Read More about The Quantified Outpatient - Challenges and Opportunities in 24hr Patient Monitoring.

Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance (2017)
Presentation / Conference Contribution
Ragab Sayed, M., Yuting Lim, R., Mandal, B., Li, L., Hwee Lim, J., & Sim, T. (2017, March). Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance. Presented at 2017 AAAI Spring Symposium, Stanford University, USA

Researchers have conducted many studies on human attentions and their eye gaze patterns for face recognition (FR), hoping to inspire new ideas to develop computer vision (CV) algorithms which perform like or even better than human. Yet, while these s... Read More about Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance.

Magnetic polarizability tensors for low frequency object classification and detection (2017)
Presentation / Conference Contribution
Ledger, P. D., & Lionheart, W. R. B. (2017, March). Magnetic polarizability tensors for low frequency object classification and detection. Paper presented at 2017 International Applied Computational Electromagnetics Society Symposium - Italy (ACES), Florence

There is considerable interest in obtaining a low-cost mathematical description, which describes the interaction between a low frequency alternating magnetic field and a conducting object. Electrical engineers have proposed that the voltage perturbat... Read More about Magnetic polarizability tensors for low frequency object classification and detection.

GLAUCOMA DIAGNOSIS USING FEATURE LEARNING BASED ON CONVOLUTIONAL NEURAL NETWORK (2016)
Presentation / Conference Contribution
Al-Bander, B., Al-Nuaimy, W., Al-Taee, M., & Zheng, Y. (2016, December). GLAUCOMA DIAGNOSIS USING FEATURE LEARNING BASED ON CONVOLUTIONAL NEURAL NETWORK

Glaucoma is one of the common causes of blindness worldwide. It leads to deterioration in vision and quality of life if it is not cured early. This paper addresses the feasibility of developing an automatic feature learning technique for detecting gl... Read More about GLAUCOMA DIAGNOSIS USING FEATURE LEARNING BASED ON CONVOLUTIONAL NEURAL NETWORK.