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BRI506 - Introduction to Pattern Recognition, Fall 2009

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This course investigates the basic concepts and methodologies of pattern recognition. In particular, this course focuses on the core theories of pattern recognition, such as Bayesian decision theory, Bayesian parameter estimation, non-parameter estimation, linear discriminant function, neural network, and statistical machine learning.

Level

Graduate

Instructor

Professor Anil K. Jain, Ph.D.

Course Description

This course investigates the basic concepts and methodologies of pattern recognition. In particular, this course focuses on the core theories of pattern recognition, such as Bayesian decision theory, Bayesian parameter estimation, non-parameter estimation, linear discriminant function, neural networks, and statistical machine learning.

Course Structure

75 minute long classes, twice a week

Copyright 2009, by the Contributing Authors. Cite/attribute Resource. Jain, A. K., kuocw. (2010, April 02). Introduction to Pattern Recognition. Retrieved August 20, 2014, from Korea University OpenCourseWare Web site: http://ocw.korea.edu/ocw/college-of-engineering/introduction-to-pattern-recognition. This work is licensed under a Creative Commons License Creative Commons License