Abstract: Researchers confront significant challenges when classifying and modeling data due to the growing system complexity, data volume, and requirement for accurate and reliable models.

This paper presents ConvAttentionNet, a lightweight and high performing deep learning model developed for accurate and efficient classification of Polarimetric Synthetic Aperture Radar (PolSAR) ...

Data center capacity has become a barometer for both the health of the tech market and the risk of an A.I. bubble. By Ian Frisch Trillions of dollars are flowing into the data centers needed to power ...

Abstract: Class imbalance can substantially affect classification tasks using traditional classifiers, especially when identifying instances of minority categories. In addition to class imbalance, ...

In today's digital landscape, organizations face an unprecedented challenge: managing and protecting ever-growing volumes of data spread across multiple environments. As someone deeply involved in ...

Many academic institutions apply their data classification schemas in service of a range of institutional functions. At UW–Madison, for example, we use data classification in the following ways: With ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Multiclass data sets and large-scale studies are increasingly common in omics sciences ...