Institute of Science and Technology · Computer Science and Engineering (%30 English) · Master
Course Objective
The focus of this course is on the theory and application of pattern recognition techniques. Topics covered include machine pattern classification, feature extraction, object recognition, Bayesian decision theory, parametric and non-parametric pattern recognition, supervised and unsupervised pattern recognition, and an overview of these topics is provided.
Course Content
Learning and adaptation, Bayesian decision theory, discriminant functions, parametric techniques, maximum likelihood estimation, Bayesian estimation, adequate statistics, non-parametric techniques, linear discriminant functions, algorithm-independent machine learning, classifiers, unsupervised learning, grouping.