SubjectsSubjects(version: 850)
Course, academic year 2019/2020
   Login via CAS
Machine learning in computer vision - NPGR035
Title in English: Strojové učení v počítačovém vidění
Guaranteed by: Department of Software and Computer Science Education (32-KSVI)
Faculty: Faculty of Mathematics and Physics
Actual: from 2019 to 2019
Semester: winter
E-Credits: 5
Hours per week, examination: winter s.:2/2 C+Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Guarantor: doc. RNDr. Elena Šikudová, Ph.D.
Annotation -
Last update: RNDr. Tomáš Holan, Ph.D. (08.10.2019)
Course is focused on image recognition. Practical part takes place in a computer lab equipped with Matlab (“Image processing” and “Computer vision” toolboxes).
Course completion requirements -
Last update: doc. RNDr. Elena Šikudová, Ph.D. (04.06.2018)

http://cgg.mff.cuni.cz/~sikudova/#teaching

Literature -
Last update: T_KSVI (11.05.2017)

Pattern classification / Richard O. Duda, Peter E. Hart, David G. Stork. New York : Wiley Interscience, 2001

Classification pattern recognition and reduction of dimensionality / edited by P. R. Krishnaiah, L. N. Kanal. Amsterdam : North-Holland, 1982

Modern multivariate statistical techniques : Regression, classification, and manifold learning / Alan Julian Izenman. New York : Springer, 2008

Requirements to the exam - Czech
Last update: doc. RNDr. Elena Šikudová, Ph.D. (17.06.2019)

znalost látky probírané na přednáškách

Syllabus -
Last update: doc. RNDr. Elena Šikudová, Ph.D. (28.09.2018)

Classification task, feature- and syntax- based object description.

Feature selection and preprocessing.

Classifiers, basic definitions.

Bayesian decision theory, discriminant functions, separating hypersurfaces, minimum error criterion.

Decision trees.

Discriminant analysis, linear classifier.

Support Vector Machines (SVM).

Neural nets.

Unsupervised learning.

Hidden Markov models.

Classification quality evaluation.

Syntactic pattern recognition, grammatical inference. Special grammar types.

 
Charles University | Information system of Charles University | http://www.cuni.cz/UKEN-329.html