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CS 326 Introduction to Computer Vision Pattern Recognition

Course Description: This course introduces the student to computer vision algorithms, methods and concepts, which will enable the student to implement computer vision systems with emphasis on visual pattern recognition. Upon successful completion of this course of study, a student will have general knowledge of image analysis and processing, pattern recognition techniques, and some experience with research in computer vision. Topics to be studied: data structures for visual pattern representation, future extraction, basis theory, decision trees, nearest neighbor, artificial neural networks, clustering, etc. The students, once completing the course, should be competent enough to conduct research in this area. The students will be required to critique a current paper from the literature in this area, present it to the class, implement the presented algorithm and evaluate the strengths and shortcomings.
br /> Course Rotation: Spring

Credits

4 credits

Prerequisite

CS 241 Minimum Grade of D