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The course is focused on basic machine learning algorithms used in computer vision tasks.
Practical part takes place in a computer lab equipped with Python.
Last update: Holan Tomáš, RNDr., Ph.D. (07.03.2024)
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http://cgg.mff.cuni.cz/~sikudova/#teaching Last update: Šikudová Elena, doc. RNDr., Ph.D. (04.06.2018)
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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 Last update: T_KSVI (11.05.2017)
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znalost látky probírané na přednáškách Last update: Šikudová Elena, doc. RNDr., Ph.D. (17.06.2019)
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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. Last update: Šikudová Elena, doc. RNDr., Ph.D. (28.09.2018)
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