Image segmentation continues to be a fundamental problem in computer vision and image understanding. In this thesis, we present a Bayesian network that we use for object boundary detection in which the MPE (most probab ...

Linear transformation for dimension reduction is a well established problem in the field of machine learning. Due to the numerous observability of parameters and data, processing of the data in its raw form is computatio ...

Parallel computers are classified into: Multiprocessors, and multicomputers. A multiprocessor system usually has a shared memory through which its processors can communicate. On the other hand, the processors of a mult ...

Data can be represented in multiple views. Traditional multi-view learning methods (i.e., co-training, multi-task learning) focus on improving learning performance using information from the auxiliary view, although info ...

The primary objective of the thesis research is to study novel schemes of on-chip crosstalk suppression employing magnetic films at microwave frequencies. Since extraction of various material properties of the magnetic f ...

The objective of this work is to explore the feasibility of replacing conventional op-amps with inverters in switched-capacitor (SC) circuits. In order to verify the idea, a low-pass filter (LPF) and a second-order del ...

A state of the art motor testing facility has been built at Oregon State University. This is the largest independent testing laboratory of its type in the western United States. The construction was funded by a consort ...

Probabilistic inference using Bayesian networks is now a well-established approach for reasoning under uncertainty. Among many e ciency-driven tech- niques which have been developed, the Optimal Factoring Problem (OFP) ...

Many different types of distributed batch scheduling systems have been developed in the last decade to take advantage of the decentralization of computers and the enormous investments that many companies and educationa ...