96 citations · 311 across the 20 of their papers we have counts for
5 papers · 1 filter
A Unified Deep Learning Approach for Prediction of Parkinson's Disease
James Wingate, Ilianna Kollia, Luc Bidaut +1
The paper presents a novel approach, based on deep learning, for diagnosis of Parkinson's disease through medical imaging. The approach includes analysis and use of the knowledge e…
Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
Bashar Alhnaity, Simon Pearson, Georgios Leontidis +1
Effective plant growth and yield prediction is an essential task for greenhouse growers and for agriculture in general. Developing models which can effectively model growth and yie…
Capsule Routing via Variational Bayes
Fabio De Sousa Ribeiro, Georgios Leontidis, Stefanos Kollias
Capsule networks are a recently proposed type of neural network shown to outperform alternatives in challenging shape recognition tasks. In capsule networks, scalar neurons are rep…
A Scalable Test Suite for Continuous Dynamic Multiobjective Optimisation
Shouyong Jiang, Marcus Kaiser, Shengxiang Yang +2
Dynamic multiobjective optimisation has gained increasing attention in recent years. Test problems are of great importance in order to facilitate the development of advanced algori…
Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks
Ilianna Kollia, Andreas-Georgios Stafylopatis, Stefanos Kollias
This paper presents a new method for medical diagnosis of neurodegenerative diseases, such as Parkinson's, by extracting and using latent information from trained Deep convolutiona…