Electrical and Computer Engineering Graduate With Thesis
Course Details

KTO KARATAY UNIVERSITY
Graduate Education Institute
Programme of Electrical and Computer Engineering Graduate With Thesis
Course Details
Graduate Education Institute
Programme of Electrical and Computer Engineering Graduate With Thesis
Course Details

| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 80511111 | Pattern Recognition | 2023 | Autumn | 1 | 3+0+0 | 7,5 | 7,5 |
| Course Type | Elective |
| Course Cycle | Master's (Second Cycle) (TQF-HE: Level 7 / QF-EHEA: Level 2 / EQF-LLL: Level 7) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | - |
| Instructor(s) | Assoc. Prof. Ali ÖZTÜRK |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Assoc. Prof. Ali ÖZTÜRK | - | [email protected] |
Course Content
Classifiers based on Bayesian decision theory, linear classifiers, non-linear classifiers, feature extraction, feature selection, dimensionality reduction, clustering
Objectives of the Course
Teaching the basics of statistical and structural pattern recognition, Bayesian decision theory, linear and non-linear classifiers, feature extraction and feature selection methods, dimensionality reduction, clustering algorithms and their application to real world problems.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Statistical and structural pattern recognition |
| 2 | Bayesian classifiers |
| 3 | Bayesian classifiers |
| 4 | Linear classifiers |
| 5 | Doğrusal olmayan sınıflandırıcılar |
| 6 | Nonlinear classifiers |
| 7 | Feature selection |
| 8 | Feature extraction |
| 9 | Dimensionality reduction |
| 10 | Template matching |
| 11 | Clustering algorithms: Sequential algorithms |
| 12 | Clustering algorithms: Hierarchical algorithms |
| 13 | Clustering algorithms: Function Optimization based algorithms |
| 14 | Cluster validity |
Textbook or Material
| Resources | S. Theodoridis, K. Koutroumbas, Pattern Recognition, 3rd edition, Academic Press, 2006. |
| S. Theodoridis, K. Koutroumbas, Pattern Recognition, 3rd edition, Academic Press, 2006. | |
| S. Theodoridis, K. Koutroumbas, Pattern Recognition, 3rd edition, Academic Press, 2006. | |
| S. Theodoridis, K. Koutroumbas, Pattern Recognition, 3rd edition, Academic Press, 2006. |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 0 | 0 | 0 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 131 | 131 |
| Other | 1 | 10 | 10 |
| Total Work Load: | 225 | ||
| Total Work Load / 30 | 7,50 | ||
| Course ECTS Credits: | 8 | ||
