Georgios Papamakarios

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Chronic obstructive pulmonary disease (COPD) is characterised by increased oxidative stress. Dietary factors, such as ample consumption of foods rich in antioxidants, such as fruit and vegetables, might have beneficial effects in COPD patients. The association between dietary shift to foods rich in antioxidants and lung function in COPD was investigated in(More)
The robust estimation of the low-dimensional subspace that spans the data from a set of high-dimensional, possibly corrupted by gross errors and outliers observations is fundamental in many computer vision problems. The state-of-the-art robust principal component analysis (PCA) methods adopt convex relaxations of 0 quasi-norm-regularised rank minimisation(More)
word count 200, Text word count 3558 E. Keranis has no conflicts of interest to disclose. D. Makris has no conflicts of interest to disclose, P. Rodopoulou has no conflicts of interest to disclose, H. Abstract Chronic obstructive pulmonary disease (COPD) is characterized by increased oxidative stress. Dietary factors such as ample consumption of foods rich(More)
In-house automatic activity detection is highly important toward the automatic evaluation of the resident's cognitive state. However, current activity detection systems suffer from the demand for on-site acquisition of large amounts of ground truth data for training purposes, which poses a major obstacle to their real-world applicability. In this paper,(More)
This paper presents a tool to support and monitor the execution of common physical exercise interventions targeting people with Mild Cognitive Impairment (MCI), Alzheimer's disease (AD) and elderly in general. Our tool aims (a) to stimulate and guide patients within physical exercise programs , (b) to monitor patient capacity to perform exercises suggested(More)
Robust low-rank modelling has recently emerged as a family of powerful methods for recovering the low-dimensional structure of grossly corrupted data, and has become successful in a wide range of applications in signal processing and computer vision. In principle, robust low-rank modelling focuses on decomposing a given data matrix into a low-rank and a(More)
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