Covid-19 has become a worldwide epidemic which has caused the death of millions in a
very short time. This disease, which is transmitted rapidly, has mutated and different …

This study proposes a new deep learning-based method that demonstrates high
performance in detecting Covid-19 disease from cough, breath, and voice signals. This …

In the area of medical imaging, one of the factors that can negatively influence the
performance of prediction algorithms is the limited number of observations for each class …

Semisupervised deep learning (SSDL) is a popular strategy to leverage unlabeled data for
machine learning when labeled data is not readily available. In real-world scenarios …

Graph-based semi-supervised classification is widely used because it effectively exploits the
characteristics of unlabeled data. However, the existing methods have a drawback in that …

Acne vulgaris is a common skin disease among adolescents. Accurate classification of acne
severity is critical to patient treatment. Most existing acne severity classification models …

In this work, we explore the problem of complex text detection. This problem is a frequent
challenge when implementing text simplification pipelines. Identifying complex text …

Semi-supervised learning (SSL) leverages both labeled and unlabeled data for training
models when the labeled data is limited and the unlabeled data is vast. Frequently, the …

Contrastive learning has gained significant popularity and achieved remarkable success in
learning meaningful representations in various domains. This study addresses the …

Deep semi-supervised learning (SSL) brings deep learning from lab with expensive label
data costs to real-world commercial application. Today, deep SSL is being universally …