Pattern Recognition and Computer Vision

Major: Computer Sciences
Code of subject: 7.122.03.O.57
Credits: 5.00
Department: Computer-Aided Design
Lecturer: Melnyk Mykhaylo Romanovych
Semester: 1 семестр
Mode of study: денна
Learning outcomes: The results of the completion of the module that the student should know: • modern models and methods of identification and classification; • Basic concepts and definitions of pattern recognition theory; • elements of pattern recognition; • Bias theory of decision-making; • learning theory, parametric and non-parametric classifiers, support vector methods, cluster analysis, classification, selection assessments.
Required prior and related subjects: Prerequisite: geometric modeling in designing engineering objects and systems, artificial intelligence.
Summary of the subject: Introduction to pattern recognition issues; information approach the problem of image; task of pattern recognition as one of the tasks of data analysis; recognition methods; recognition algorithms; the concept of the theory of images; job classification and recognition.
Assessment methods and criteria: Ongoing control (45%), current reports on laboratory work, oral examination, control work; Final control (55% Exam): performance tests.
Recommended books: 1. Pohrebennyk V.D. Systemy rozpiznavannya obraziv / Navch. posibnyk. – L'viv: SPOLOM, 2007. – 170 s. 2. Rozpiznavannya obraziv [Tekst] : navch. posibnyk / V.Ya. Kutkovets'kyy. - Mykolayiv : Vyd-vo MDHU im. P. Mohyly, 2003. - 196 s. 3. Lepskyy A.E., Bronevych A.H. Matematycheskye metody raspoznavanyya obrazov. (Kurs lektsyy). Yuzhnyj federal'nyj unyversytet: Tahanroh, 2009. 4. Duda R., Khart P. Raspoznavanye obrazov y analyz stsen. — M.: Myr, 1976.