25 citations · 82 across the 37 of their papers we have counts for
10 papers · 1 filter
RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization
Yan Lin, Ziheng Wang, Shuang Chen +2
Medical image classifiers are often trained within one source population, yet clinical deployment requires robustness to patients whose appearance, acquisition style, and disease p…
My Emotion on your face: The use of Facial Keypoint Detection to preserve Emotions in Latent Space Editing
Jingrui He, Andrew Stephen McGough
Generative Adversarial Network approaches such as StyleGAN/2 provide two key benefits: the ability to generate photo-realistic face images and possessing a semantically structured…
O-TALC: Steps Towards Combating Oversegmentation within Online Action Segmentation
Matthew Kent Myers, Nick Wright, A. Stephen McGough +1
Online temporal action segmentation shows a strong potential to facilitate many HRI tasks where extended human action sequences must be tracked and understood in real time. Traditi…
NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies
Atif Khan, Conor Lawless, Amy Vincent +4
Single cell analysis of human skeletal muscle (SM) tissue cross-sections is a fundamental tool for understanding many neuromuscular disorders. For this analysis to be reliable and…
Introducing NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies
Atif Khan, Conor Lawless, Amy Vincent +4
Single cell analysis of skeletal muscle (SM) tissue is a fundamental tool for understanding many neuromuscular disorders. For this analysis to be reliable and reproducible, identif…
Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets
Michael Luke Battle, Amir Atapour-Abarghouei, Andrew Stephen McGough
Skin cancer is the most common malignancy in the world. Automated skin cancer detection would significantly improve early detection rates and prevent deaths. To help with this aim,…
Towards Automatic Cetacean Photo-Identification: A Framework for Fine-Grain, Few-Shot Learning in Marine Ecology
Cameron Trotter, Nick Wright, A. Stephen McGough +6
Photo-identification (photo-id) is one of the main non-invasive capture-recapture methods utilised by marine researchers for monitoring cetacean (dolphin, whale, and porpoise) popu…
Application of deep learning to camera trap data for ecologists in planning / engineering -- Can captivity imagery train a model which generalises to the wild?
Ryan Curry, Cameron Trotter, Andrew Stephen McGough
Understanding the abundance of a species is the first step towards understanding both its long-term sustainability and the impact that we may be having upon it. Ecologists use came…
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation
Amir Atapour-Abarghouei, Stephen Bonner, Andrew Stephen McGough
Newly emerging variants of ransomware pose an ever-growing threat to computer systems governing every aspect of modern life through the handling and analysis of big data. While var…
The Northumberland Dolphin Dataset: A Multimedia Individual Cetacean Dataset for Fine-Grained Categorisation
Cameron Trotter, Georgia Atkinson, Matthew Sharpe +3
Methods for cetacean research include photo-identification (photo-id) and passive acoustic monitoring (PAM) which generate thousands of images per expedition that are currently han…