Imbalanced classification problems are often encountered in many applications. The
challenge is that there is a minority class that has typically very little data and is often the …

Background Classification using class-imbalanced data is biased in favor of the majority
class. The bias is even larger for high-dimensional data, where the number of variables …

A crucial part of sentiment classification is featuring extraction because it involves extracting
valuable information from text data, which affects the model's performance. The goal of this …

Predicting the subcellular localization of proteins is an important and challenging problem.
Traditional experimental approaches are often expensive and time‐consuming …

Infertility is a social stigma for individuals, and male factors cause approximately 30% of
infertility. Despite this, male infertility is underrecognized and underrepresented as a …

Deep learning-based fault diagnosis usually requires a rich supply of data, but fault samples
are scarce in practice, posing a considerable challenge for existing diagnosis approaches to …

An important problem associated with the aerial map** of the seabed is the precise
classification of point clouds characterizing the water surface, bottom, and bottom objects …

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide.
Low-dose computed tomography (LDCT) of the chest has been proven effective in …

The health status of mechanical bearings concerns the safety of equipment usage.
Therefore, it is of crucial importance to monitor mechanical bearings. Currently, deep …

High-throughput screening (HTS) experiments provide a valuable resource that reports
biological activity of numerous chemical compounds relative to their molecular targets …