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Purpose
To assess the use of deep learning (DL) for computer‐assisted glaucoma identification, and the impact of training using images selected by an active learning strategy, which minimizes labelling cost. Additionally, this study focuses on the explainability of the glaucoma classifier.
Methods
This original investigation pooled 8433 retrospectively collected and anonymized colour optic disc‐centred...
The goal of this paper is to explore the potential of opportunistic mobile monitoring to map the exposure to air pollution in the urban environment at a high spatial resolution. Opportunistic mobile monitoring makes use of existing mobile infrastructure or people’s common daily routines to move measurement devices around. Opportunistic mobile monitoring can also play a crucial role in participatory...
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