MATH 445 - Image Analysis & Pattern Recog

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Description

Hours: Three hours lecture in the lab per week Prerequisite: PHYS/COMP/MATH 345 or consent of the instructor Description: The course addresses the issue of analyzing the pattern content within an image. Pattern recognition consists of image segmentation, feature extraction and classification. The principles and concepts underpinning pattern recognition, and the evolution, utility and limitations of various techniques (including neural networks) will be studied. Programming exercises will be used to implement examples and applications of pattern recognition processes, and their performance on a variety of diverse synthetic and real images will be studied.

Units: 3.00
Grading: Letter Grade

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Session Section Class # Type Days Time Location Instructor Course Details [Key]
1 01 2071 LEC W  6:00 PM  -  8:50 PM  Sierra Hall 2111 William Barber Course Open Class Details In Person Class

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