This page refers to the Spring 2017 offering of CSE 555 only. The information on this page does not necessarily apply to every offering of CSE 555.
Introduction to Pattern Recognition
Foundations of pattern recognition algorithms and machines, including statistical and structural methods. Data structures for pattern representation, feature discovery and selection, classification vs. description, parametric and non-parametric classification, supervised and unsupervised learning, use of contextual evidence, clustering, recognition with strings, and small sample-size problems. programming projects.
2 years of college mathematics, including probability theory.
Ph.D.: This course fulfills one Artificial Intelligence Core Course (Breadth) requirement.
M.S.: This course fulfills one Artificial Intelligence Core Course (Breadth) requirement.