Class Number: 2500
Description: Hours: Three hours lecture in the lab per week. Prerequisites: Admission to the Computer Science or Mathematics Graduate Program New and emerging applications of pattern recognition (PR) such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition - require robust and efficient techniques. Statistical decision making and estimation are fundamental to the study of PR. Pattern content is analyzed using feature extraction and classification. The principles and concepts underpinning PR, 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 PR processes, and their performance on a variety of diverse examples will be studied.

Info has been updated in the last 30 minutes
Days Time Date Range Location Instructor
TH 06:00 PM - 08:50 PM 01/20/2024 - 05/17/2024 Del Norte Hall 1550 William Barber
Status: Open
Session: Extended Session 1
Units: 3.00
Class Components: Lecture
Career: Postbaccalaureate
Start Date: 01/20/2024
End Date: 05/17/2024
Grading: Letter Grade

Class Availability

Information below is 24 hours old.
Enrollment Total: 22
Available Seats: 2
Wait List Capacity: 5
Wait List Total: 0


Textbook / Other Materials

Textbook Status: Required
ISBN: 9781461453239
Title: Pattern Recognition and Classification
Author: Dougherty
Publish: Springer Nature

Textbook Status: Required
ISBN: 9781107713918
Title: Digital Image Processing for Medical Applications
Author: Dougherty
Publish: CAMBRIDGE UNIV PRESS

Textbook Status: Required
ISBN: 9780521860857
Title: Digital Image Processing for Medical Applications
Author: Dougherty
Publish: CAMBRIDGE UNIV PRESS

Textbook Status: Required
ISBN: 9781461453222
Title: Pattern Recognition & Classification: An Introduct
Author: Doughtery
Publish: Springer Nature

More textbook information including prices

Enrollment Information

  • Graduate Division
  • In-Person


Notes

  • Cross-listed course
Back to Top ↑