CS 6720 - Pattern Recognition

A survey of modern methods for computer recognition of patterns in varied applications such as digital images, human speech and sound, and grammar-based sequences. Various approaches are developed, including heuristic search, Fourier analysis, Markov models, template matching, and grammatical inference. Computational aspects and efficiency of different methods and algorithms are emphasized. Students must complete a project using methods developed in the course.

Prerequisites/Corequisites: Prerequisites: (CS 4310 or CS 5310) and undergraduate-level statistics, a grade of “B” or better is required to satisfy any course prerequisite.

Credits: 3 hours

Restrictions This course is restricted to the following: masters and doctorates in computer science, masters in electrical engineering, and doctorates in mathematics.
Notes: Open to graduate students only.