Recent advances in computer vision are primarily driven by the usage of deep learning,
which is known to require large amounts of data, and creating datasets for this purpose is …

Featured Application This article assesses different text representations for labeling
unmarked dialog data, which can be applied to identify user intents directly relevant to …

We present a novel information-theoretic framework, termed as TURBO, designed to
systematically analyse and generalise auto-encoding methods. We start by examining the …

A deep learning classifier is proposed for grading hypoxic-ischemic encephalopathy (HIE) in
neonates. Rather than using handcrafted features, this architecture can be fed with raw EEG …

Establishing sustainable plantations with genetic diversity equivalent to that of natural
populations is vital for successful reforestation efforts. In this study, we present an innovative …

Neurocognitive Disorders (NCDs) pose a significant global health concern, and early
detection is crucial for optimizing therapeutic outcomes. In parallel, mobile health apps …

The mechanisms involved in the homogeneous perception of odorant mixtures remain
largely unknown. With the aim of enhancing knowledge about blending and masking …

Domain shift is one of the key challenges affecting reliability in medical imaging-based
machine learning predictions. It is of significant importance to investigate this issue to gain …