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Viewing: ECE 6850 : Pattern Recognition

Last approved: Tue, 07 Mar 2017 09:04:29 GMT

Last edit: Sat, 25 Feb 2017 21:23:30 GMT

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In The Catalog Prerequisites:

ECE 6885 : Computer Vision

As A Banner Equivalent:

BME 6850 : Pattern Recognition
School of Engineering and Applied Sciences
Electrical and Computer Engineering (ECE)
ECE
6850
Pattern Recognition
Pattern Recognition
Fall 2017
3
Course Type
Lecture
Default Grading Method
Letter Grade

No
No
ECE 6015
Corequisites

20

Frequency of Offering
Odd Years
Term(s) Offered
Fall
Are there Course Equivalents?
No
 
No
Fee Type


No


Random vectors, transformations; hypothesis testing, error probability, sequential methods. Bayes, other linear classifiers; discriminant functions, parameter estimation, learning, and dimensionality reduction; nonparametric methods; clustering; feature selection and ordering; computer applications and projects.
As a result of completing this course, students will be able to:
1. understand and apply decision theory, parameter estimation, and nonparametric methods
2. understand and apply feature extraction, data representation, and dimensionality reduction
3. understand and develop methods for classification, including discriminant functions and support-vector machines
4. use unsupervised techniques (learning, clustering) and evaluate classifier performance
Uploaded a Course Syllabus

Course Attribute


Key: 2478