MATH 445 - Image Analysis & Pattern Recog

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.

Meeting Information

Status: Open
Class Number: 2071
Session: Regular Academic Session
Units: 3.00
Class Components: Lecture
Career: Undergraduate
Dates: 1/20/2024 - 5/17/2024
Grading: Letter Grade

Class Availability

Information below is 24 hours old.
Enrollment Total: 11
Available Seats: 13
Wait List Capacity: 0
Wait List Total: 0

Textbook / Other Materials

Enrollment Information

• Upper Division

Notes