Classification of images in many category datasets has
rapidly improved in recent years. However, systems that
perform well on particular datasets typically have one or
more lim...
Many perceptual models and theories hinge on treating objects as a collection of constituent parts. When applying these approaches to data, a fundamental problem arises: how can w...
The paper describes an ontology-based framework for bridging learning design and learning object content. In present solutions, researchers have proposed conceptual models and dev...
We study suitable indexing techniques to support efficient exact match search in large biological sequence databases. We propose a suffix tree (ST) representation, called STA-DF, ...
Mihail Halachev, Nematollaah Shiri, Anand Thamildu...
We study how the error of an ensemble regression estimator can be decomposed into two components: one accounting for the individual errors and the other accounting for the correlat...