Subject

Introduction to Pattern Recognition

Course Title

Introduction to Pattern Recognition
Introduction to Pattern Recognition

Code

F18L3W089

Study Programme

—

Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

First Cycle

Academic year / semester

7 / Winter

Number of ECTS credits

Teacher

—

Prerequisites for enrolling in the course

Machine learning

10.

Objectives of the course programme (competences)

The goal of the course is for students to learn the main concepts of the methods and techniques that are applied for
shape recognition. Upon completion of the course, candidates will be qualified to design,
realization and implementation of systems for automatic shape recognition, assessment of their
performance and their optimization.

11.

Course content

Introduction to the problem of pattern recognition. Machine perception, components of a pattern recognition system. Types of features, feature extraction, feature selection, and feature generation. Classifiers based on Bayes' decision theory, linear classifiers, nonlinear classifiers. Methods for unsupervised learning. Design and implementation of a pattern recognition system. System performance evaluation. Application examples in identification and authentication systems, medical diagnostics, defense, bioinformatics, text recognition, handwriting, face recognition, fingerprint recognition, biometric data, speech recognition, and text classification.

12.

Learning methods

lectures, classroom exercises, laboratory exercises, project assignments, homework

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	30 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	45 hours

16.

Other forms of activities

16.1.	Project assignments	15 hours
16.2.	Independent assignments	15 hours
16.3.	Home study	75 hours

17.

Assessment method

17.1.	Tests	10 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activities and learning	10 points
17.4.	Final exam	70 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

Completed activities 15, 16

20.

Language of instruction

Macedonian and English

21.

Method for monitoring the quality of teaching

internal evaluation and surveys

22.

Literature

22.1.	Required literature No. Author Title Publisher Year
22.2.	Additional literature No. Author Title Publisher Year