Soft sensors for regression applications (SSR) are inferential models that use online
available sensors (eg temperature, pressure, flow rate, etc.) to predict quality variables …

The goal of this article is to review the state-of-the-art tracking methods, classify them into
different categories, and identify new trends. Object tracking, in general, is a challenging …

In the DNA microarray research field, the increasing sample size and feature dimension of
the gene expression data prompt the development of an efficient and robust feature …

Decision support systems help physicians and also play an important role in medical
decision-making. They are based on different models, and the best of them are providing an …

Support vector machine (SVM) is a supervised machine learning approach that was
recognized as a statistical learning apotheosis for the small-sample database. SVM has …

The increasing power of computer technology does not dispense with the need to extract
meaningful information out of data sets of ever growing size, and indeed typically …

Missing data is a common drawback in many real-life pattern classification scenarios. One of
the most popular solutions is missing data imputation by the K nearest neighbours (KNN) …

Background At present, the only way to conclusively diagnose endometriosis is laparoscopic
inspection, preferably with histological confirmation. This contributes to the delay in the …

As one of the core applications of computer vision, object detection has become more
important in scenarios requiring high accuracy but with limited computational resources …

Allostery describes altered protein function at one site due to a perturbation at another site.
One mechanism of allostery involves correlated motions, which can occur even in the …