Background The life sciences, biomedicine and health care are increasingly turning into a
data intensive science [2–4]. Particularly in bioinformatics and computational biology we …

Real-world classification problems typically exhibit an imbalanced or long-tailed label
distribution, wherein many labels are associated with only a few samples. This poses a …

Computerization in healthcare in general, and in the operating room (OR) and intensive care
unit (ICU) in particular, is on the rise. This leads to large patient databases, with specific …

The conventional detectors tend to make imbalanced classification and suffer performance
drop, when the distribution of the training data is severely skewed. In this paper, we propose …

Real-world datasets are typically imbalanced in the sense that only a few classes have
numerous samples, while many classes are associated with only a few samples. As a result …

With millions of users tweeting around the world, real time search systems and different
types of mining tools are emerging to allow people tracking the repercussion of events and …

An automatic method for recognizing natively disordered regions from amino acid sequence
is described and benchmarked against predictors that were assessed at the latest critical …

Face recognition presents a challenging problem in the field of image analysis and
computer vision, and as such has received a great deal of attention over the last few years …

Text Classification, or the task of automatically assigning semantic categories to natural
language text, has become one of the key methods for organizing online information. Since …

Support Vector Tracking (SVT) integrates the Support Vector Machine (SVM) classifier into
an optic-flow-based tracker. Instead of minimizing an intensity difference function between …