XP33ROD - Pattern Recognition for doctoral students

Summer semestr 2007/2008, 2 hours lectures, personal assignment equivalent to 2 hours per week.

The lecture is given on Mondays from 9:15 to 10:45 in the seminar room G205, building G of the Faculty of Electrical Engineering at the Czech Technical University Campus at Karlovo náměstí. If there is one student enrolled who does not understand Czech then the lectures will be given in English, otherwise in Czech. Most of the presentations are in English too.

The subject XP33ROD je intended as an introductory one for doctoral students who did not pass the subject 33RPZ Pattern Recognition which is taught by Doc. Ing. Jiří Matas, PhD. in the MSc study program or those who like to see the topic through eyes of another teacher. For others,  a more advanced subject  XP33ROZ is available which is usually taught in the same semester but is not opened in Summer semester 2007/2008.

Lecturers:  

prof. Ing. Václav Hlaváč, CSc.,  prof. Ing. Vladimír Mařík, DrSc.
Katedra kybernetiky, Fakulta elektrotechnická ČVUT
hlavac@cmp.felk.cvut.cz, marik@fel.cvut.cz 


Exercises instructor:  prof. Ing. Václav Hlaváč, CSc.

Students have two options how to pass exercises.

  1. Participate in the exercises taught for master students in the subject 33RPZ. Make your arrangements with the instructors of the subject and inform me (V. Hlaváč) about it before you start attending the exercises. The content of exercises can be modified according to previous experience of the student and according to student's research interest.
  2. Solve an individual assignment which is related to the subject. This option has to be negotiated in advanced with V. Hlaváč.

Praha, February 18, 2008

 

Plan of the lectures

Week of a semester

Lecturer

Date

Topic of the lecture

1 no one 25.02.2008 No lecture. V. Hlaváč is on the business trip abroad.
2 V. Hlaváč 3.03.2008 Introduction. Basic concepts. Formulation of the basic tasks solved in pattern recognition. Rehearsal of basic knowledge from probability theory and statistics.
3 J. Matas 10.03.2008 Bayesian task. Overview of non-Bayesian tasks.
4 V. Hlaváč 17.03.2008 Experimental evaluation of classifiers. Receiver operator curve (ROC).
5 no one 24.03.2008 Holiday. Easter Monday.
5 V. Mařík 31.03.2008 Structural pattern recognition, a classical approach.
6 V. Hlaváč 7.04.2008 Two special useful statistical models. Conditional independence of features. Gaussian models. Strightening of the feature space.
7 V. Hlaváč 14.04.2008 Estimation of probabilistic models. Parametric and nonparametric methods.
8 V. Hlaváč 21.04.2008 Learning in pattern recognition. VC dimension. Estimate of the needed length of the training sequence.
9 V. Hlaváč 28.04.2008  Linear classifiers and their learning.
10 V. Hlaváč 5.05.2008  Support vector machines classifiers (SVM).
11  V. Hlaváč  12.05.2008  Kernel methods.
12  V. Hlaváč

19.05.2008

Recognition of Markovian sequences.
13 J. Matas 26.05.2008 Unsupervised learning. Cluster analysis. EM (Expectation Maximization) algorithm.
  no one 2.06.2008 No lecture because of V. Hlavac's business trip.
addition V. Hlaváč 9.06.2008 15:00 Relation between statistical and structural pattern recognition.

Recommended literature:

  1. Schlesinger M.I., Hlaváč V.: Ten lectures on statistical and structural pattern recognition, Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002. Edition in Czech Vydavatelství ČVUT Praha, 1999.
  2. Duda R.O., Hart, P.E.,Stork, D.G.: Pattern Classification, John Willey and sons, 2nd edition, New York, 2001.
  3. Bishop, C.M: Pattern Recognition and Machine Learning, Springer, New York, 2006.

Students of the subject:

Presentations (It is likely that presentation will be updated before the lecture):

Follow the www pages with my presentation I maintain: in English, in Czech.

Poslední změna 25.05. 2008 V. Hlaváč, hlavac@fel.cvut.cz