no code implementations • 1 Mar 2021 • Jonathan Frawley, Chris G. Willcocks, Maged Habib, Caspar Geenen, David H. Steel, Boguslaw Obara
Macular holes are a common eye condition which result in visual impairment.
no code implementations • 23 Oct 2020 • John Brennan, Stephen Bonner, Amir Atapour-Abarghouei, Philip T Jackson, Boguslaw Obara, Andrew Stephen McGough
With the growing significance of graphs as an effective representation of data in numerous applications, efficient graph analysis using modern machine learning is receiving a growing level of attention.
no code implementations • 16 Jul 2020 • Philip T. Jackson, Stephen Bonner, Ning Jia, Christopher Holder, Jon Stonehouse, Boguslaw Obara
We show that correlations between the camera used to acquire an image and the class label of that image can be exploited by convolutional neural networks (CNN), resulting in a model that "cheats" at an image classification task by recognizing which camera took the image and inferring the class label from the camera.
no code implementations • 10 May 2020 • Jonathan Frawley, Chris G. Willcocks, Maged Habib, Caspar Geenen, David H. Steel, Boguslaw Obara
This paper investigates the application of deep convolutional neural networks with prohibitively small datasets to the problem of macular edema segmentation.
1 code implementation • 21 Aug 2019 • Stephen Bonner, Amir Atapour-Abarghouei, Philip T. Jackson, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Graphs have become a crucial way to represent large, complex and often temporal datasets across a wide range of scientific disciplines.
Social and Information Networks
1 code implementation • 28 Apr 2019 • Fady Medhat, Mahnaz Mohammadi, Sardar Jaf, Chris G. Willcocks, Toby P. Breckon, Peter Matthews, Andrew Stephen McGough, Georgios Theodoropoulos, Boguslaw Obara
In this work, we present a generic process flow for text recognition in scanned documents containing mixed handwritten and machine-printed text without the need to classify text in advance.
no code implementations • 15 Mar 2019 • Philip T. Jackson, Yinhai Wang, Sinead Knight, Hongming Chen, Thierry Dorval, Martin Brown, Claus Bendtsen, Boguslaw Obara
While deep learning has seen many recent applications to drug discovery, most have focused on predicting activity or toxicity directly from chemical structure.
1 code implementation • 1 Feb 2019 • Haifa F. Alhasson, Shuaa S. Alharbi, Boguslaw Obara
The detection of vascular structures from noisy images is a fundamental process for extracting meaningful information in many applications.
1 code implementation • 20 Nov 2018 • Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Graphs are a commonly used construct for representing relationships between elements in complex high dimensional datasets.
1 code implementation • 23 Sep 2018 • Shuaa S. Alharbi, Cigdem Sazak, Carl J. Nelson, Boguslaw Obara
The proposed approach is validated on synthetic and real data and is also compared to the state-of-the-art approaches.
1 code implementation • 14 Sep 2018 • Philip T. Jackson, Amir Atapour-Abarghouei, Stephen Bonner, Toby Breckon, Boguslaw Obara
In addition to standard classification experiments, we investigate the effect of style augmentation (and data augmentation generally) on domain transfer tasks.
2 code implementations • 19 Jun 2018 • Stephen Bonner, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
To explore this, we present extensive experimental evaluation from five state-of-the-art unsupervised graph embedding techniques, across a range of empirical graph datasets, measuring a selection of topological features.
no code implementations • 14 Feb 2018 • Cigdem Sazak, Carl J. Nelson, Boguslaw Obara
Enhancement and detection of 3D vessel-like structures has long been an open problem as most existing image processing methods fail in many aspects, including a lack of uniform enhancement between vessels of different radii and a lack of enhancement at the junctions.
no code implementations • 16 Sep 2017 • Çiğdem Sazak, Carl J. Nelson, Boguslaw Obara
Enhancement, followed by segmentation, quantification and modelling, of blood vessels in retinal images plays an essential role in computer-aid retinopathy diagnosis.