Course No: 0907542
Course Name: Pattern Recognition

Facebook group: https://www.facebook.com/groups/196796377198206/ 

Department Announcement Page: http://www.facebook.com/pages/Computer-Engineering-Department/369639656466107

Handouts:

• Course Syllabus (pdf)
• Project Report Guidelines (ppt)
• Slides:
• Course Introduction (ppt)
• Introduction (ppt)
• Bayes Classifiers (ppt)
• Linear Classifiers (ppt)
• Nonlinear Classifiers (ppt)
• Feature Selection (ppt)
• Feature Generation (ppt)
• Template Matching (ppt)
• Context Dependent Classification (ppt)
• System Evaluation (ppt)
• Clustering Algorithms (ppt)
• Clustering Techniques (ppt)

Demonstrations:

• Matlab Pattern Classification 1
• Matlab Pattern Classification 2
• Feature Extraction
• Feature Selection (Slides)
• Matlab Pattern Classification 3

Suggested problems:

• Chapter 2: 2.2, 2.7, 2.8, 2.12, 2.31
• Chapter 3: 3.4, 3.6, 3.9 (Some problems require programming)
• Chapter 4: 4.1, 4.3

Important Links:

• Textbook Web Site
• Pattern Classification (2nd ed) by Richard O. Duda, Peter E. Hart and David G. Stork
• Pattern Recognition Course (CSE802) by Dr. Anil Jain
• Machine Learning Course (CS 229) by Dr. Andrew Ng

Links to Items Used in the Last Lecture:

• Pattern Recognition Presentation by Nick Lund
• 15 Current Technologies A Child Born Today Will Never Use
• Introducing the Google’s Knowledge Graph
• Do Androids Dream of Stealing Your Job?
• Future Technology Watch your day in 2020

Solutions:

• Midterm exam (pdf)

Grades sheet including midterm exam and the course project (pdf).

Last update on 1/6/2014, 10:12 am.