no code implementations • 13 Jun 2018 • Lorenz Berger, Eoin Hyde, Matt Gibb, Nevil Pavithran, Garin Kelly, Faiz Mumtaz, Sébastien Ourselin
Training deep neural networks on large and sparse datasets is still challenging and can require large amounts of computation and memory.
no code implementations • 2 May 2018 • Luis C. Garcia-Peraza-Herrera, Martin Everson, Wenqi Li, Inmanol Luengo, Lorenz Berger, Omer Ahmad, Laurence Lovat, Hsiu-Po Wang, Wen-Lun Wang, Rehan Haidry, Danail Stoyanov, Tom Vercauteren, Sebastien Ourselin
We present a new approach to visualise attention that aims to give some insights on those areas of the oesophageal tissue that lead a network to conclude that the images belong to a particular class and compare them with those visual features employed by clinicians to produce a clinical diagnosis.
no code implementations • 8 Sep 2017 • Lorenz Berger, Eoin Hyde, M. Jorge Cardoso, Sebastien Ourselin
Deep convolutional neural networks (CNNs) have shown excellent performance in object recognition tasks and dense classification problems such as semantic segmentation.