23 citations · 87 across the 24 of their papers we have counts for
5 papers · 1 filter
Exploring Motion Boundaries in an End-to-End Network for Vision-based Parkinson's Severity Assessment
Amirhossein Dadashzadeh, Alan Whone, Michal Rolinski +1
Evaluating neurological disorders such as Parkinson's disease (PD) is a challenging task that requires the assessment of several motor and non-motor functions. In this paper, we pr…
Back to the Future: Cycle Encoding Prediction for Self-supervised Contrastive Video Representation Learning
Xinyu Yang, Majid Mirmehdi, Tilo Burghardt
In this paper we show that learning video feature spaces in which temporal cycles are maximally predictable benefits action classification. In particular, we propose a novel learni…
VI-Net: View-Invariant Quality of Human Movement Assessment
Faegheh Sardari, Adeline Paiement, Sion Hannuna +1
We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data. Our end-to-end convolutional neural network consis…
Meta-Learning with Context-Agnostic Initialisations
Toby Perrett, Alessandro Masullo, Tilo Burghardt +2
Meta-learning approaches have addressed few-shot problems by finding initialisations suited for fine-tuning to target tasks. Often there are additional properties within training d…
Prediction of Thrombectomy Functional Outcomes using Multimodal Data
Zeynel A. Samak, Philip Clatworthy, Majid Mirmehdi
Recent randomised clinical trials have shown that patients with ischaemic stroke {due to occlusion of a large intracranial blood vessel} benefit from endovascular thrombectomy. How…