Class imbalance (CI) is a well-known problem in data science. Nowadays, it is affecting the
data modeling of many of the real-world processes that are being digitized. The …

The goal of lipidomic studies is to provide a broad characterization of cellular lipids present
and changing in a sample of interest. Recent lipidomic research has significantly contributed …

Facial Action Unit (AU) detection is of major importance in a broad range of artificial
intelligence applications such as healthcare, Facial Expression Recognition (FER), and …

There exists three main areas of study inside of the field of predictive maintenance: anomaly
detection, fault diagnosis, and remaining useful life prediction. Notably, anomaly detection …

Skin lesion is one of the most commonly encountered illnesses that need to be detected and
treated at an early stage. Numerous Convolutional Neural Network (CNN) classifiers were …

Defect detection is a crucial technology in the industry that enhances production efficiency
within the manufacturing sector. However, obtaining a balanced dataset with sufficient …

The accumulation of polyethylene microplastic (PE-MPs) in soil can significantly impact plant
quality and yield, as well as affect human health and food chain cycles. Therefore …

MicroRNAs (miRNA) are categorized as short endogenous non-coding RNAs, which have a
significant role in post-transcriptional gene regulation. Identifying new animal precursor …

Bluebottles (\textit {Physalia} spp.) are marine stingers resembling jellyfish, whose presence
on Australian beaches poses a significant public risk due to their venomous nature …

Imbalanced multiclass datasets pose challenges for machine learning algorithms. These
datasets often contain minority classes that are important for accurate prediction. Existing …