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Daniel B. Rowe, Ph.D.
MATH 4770/MSSC 5770: Statistical Machine Vision
There is not a required book. All material will be presented via lecture.

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Course Syllabus Summer 2024
Flyer, Syllabus, Schedule
In general class periods will alternate between lecture and coding/homework.
Occasionally more than one class period will be used to cover particular topics.
Students will submit and present their homework solutions in class via Teams and we will go through Matlab code.
All class sessions will be recorded via teams so students can view at a later time.

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Lecture Topics
Lecture 00:  Syllabus
Lecture 01:  Matlab
Lecture 02:  Within Image Processing
Lecture 03:  Image Filter Design
Lecture 04:  Statistical Implications
Lecture 05:  The Correlation Coefficient
Lecture 06:  Pixel Statistics & Template Matching
Lecture 07:  Through Image Processing
Lecture 08:  The Discrete Fourier Transform
Lecture 09: Convolution via the DFT
Lecture 10:  Fast Object Tracking
Lecture 11:  Peaks, Valleys, and Ridges
Lecture 12:  Machine Vision Summary

All topics and assignments will have a computational aspect using Matlab.

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Return to Professor Rowe's Webpage

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