Pattern Recognition and
Image Processing Group
Institute of Computer Graphics and Algorithms
Introduction to Pattern Recognition
Aim of course
This lecture teaches the basics in pattern recognition and gives an overview of the most important methods. Its focus lies on the analysis of images, i.e. extraction and processing of features, and classification of the extracted data. The corresponding exercise (186.840) deepens the understanding of the topics of the lecture.
Subject of course
Feature extraction, basics of probability theory (conditional probabilities, marginal distributions, independence, covariance matrices, etc.), Bayes theorem, simple classifiers (kNN, nearest neighbor, persceptron, etc.), ...
TUWELFor students registered in TISS a TUWEL course provides the slides of the lecture, additional material, demos, etc.
2014 PRIP, Impressum
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