ENEE739Q/CMSC858C Statistical and Neural Pattern Recognition

 

Course Basics Time: Tuesday Thursday 12:30pm-1:45pm, Fall 2003
Venue: CSI 2118
Textbook:  R. Duda, P. Hart, and D. Stork, Pattern Classification, Wiley Interscience, 2001. 
Grading Policy: Homework 15%, Midterm 25%, Final 40%, Projects 20%

 

Instructor Basics Instructor: Prof. Rama Chellappa ( rama@cfar.umd.edu )
Room 4411, A. V. Williams Bldg
Office Hours: Tuesday Thursday 2:00pm-4:00pm

Unofficial TA: Shaohua (Kevin) Zhou ( shaohua@cfar.umd.edu )
Room 4444, A. V. Williams Bldg
Office Hours: Friday 3:00pm-5:00pm

 

Course Schedule Course Schedule

 

Course Projects Course Project

 

Course Notices
  • 12/08/2003(new!) Class on 12/09/2003 has been cancelled. Prof. Chellappa will go over the final exam on this Thursday 12/11/2003.
  • 12/03/2003 two papers on geometric hashing: lamdan88iccv lamdan90tra
  • 11/26/2003  two papers on pattern recognition applications: face recognition automation target recognition
  • 11/20/2003 Slides on tree methods cart.ppt
  • 11/04/2003 A website of matrix calculus.
  • 10/23/2003 A tutorial paper on SVM. svm_pr_tutorial.pdf
  • 10/21/2003 The course project has been announced.
  • 09/30/2003 There is a temporary room change on 10/9/2003. The class will move to AVW3258. 
  • 09/26/2003 Reference on Rayleigh Quotient .
  • 09/10/2003 Thank Prof. Papamarcou for sharing his ENEE621 course note, which is an excellent reference to estimation and detection theory and a good self-start point.
  • 09/10/2003 Bhattacharyya distance does not satisfy triangle inequality. Check out Kailath's original paper and its comments. kailath67ct.pdf toussaint72ct.pdf
  • 08/25/2003 Please send your name and email to shaohua@cfar.umd.edu. I will create an email list for this class. Please broadcast this to others.

 

Accessory Links
  1. ENEE698A Graduate Seminar on Statistical Learning
  2. Textbook FAQ created by D. Stork
  3. Elements of Statistical Learning by T. Hastie, R. Tibshirani, and J. Friedman
  4. Pattern Recognition and Neural Networks by B. Ripley
  5. Pattern Recognition Information: a good website collecting a lot of useful information
  6. ENEE621 course note by Prof. Papamarcou: an excellent reference to estimation and detection theory and a good self-start point.

 


Please address your comments on this website to Shaohua (Kevin) Zhou at shaohua@cfar.umd.edu.