CS 533 / CMPE 533

Pattern Recognition

This course provides an introduction to the area of Statistical Pattern Recognition. The course will be beneficial to graduate students intending to pursue research in this area, as well as in applied fields which use pattern recognition, such as speech recognition, computer vision, image processing, signal classification, optical character recognition and data mining. Major topics covered in the course include supervised and unsupervised learning, Bayesian decision theory, parametric and non-parametric density estimation methods, linear discriminant functions and clustering methods.