ECTS - Pattern Classification and Sensor Applications for Engineers

Pattern Classification and Sensor Applications for Engineers (EE449) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Pattern Classification and Sensor Applications for Engineers EE449 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Drill and Practice.
Course Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. Hakan TORA
Course Assistants
Course Objectives Sensors, general information about sensor types and sensor working principles. What is a pattern? Pattern classification applications. Theory and methods of pattern classification. Feature extraction and selection. MATLAB Classification Learner Tool. Analysis and performance of classifiers. RFID basics.
Course Learning Outcomes The students who succeeded in this course;
  • Know about sensors.
  • Design a classifier system.
  • Analyze the performance of classifiers.
  • Design and implement a project including sensors.
  • Use the MATLAB Classification Learner application tool.
Course Content Sensors, general information about sensor types and sensor working principles; what is a pattern; pattern classification applications; theory and methods of pattern classification; feature extraction and selection; MATLAB Classification Learner Tool; analysis and performance of classifiers; RFID basics.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 What is a sensor? Obtain the reference books.
2 Sensor types. Review last week’s topics
3 Working principles of sensors. Review last week’s topics
4 What is a pattern? Review last week’s topics
5 Theory of pattern classification Review last week’s topics
6 Feature extraction. Review last week’s topics
7 Feature selection. Review last week’s topics
8 Analysis and performance of classifiers. Review last week’s topics
9 Midterm Exam Review all topics up-to this week
10 Design of an interdisciplinary project Review all topics
11 Project work continued Review all topics
12 Implementation of the project. Review all topics
13 Implementation of the project Review all topics
14 Presentations Review the project

Sources

Course Book 1. Duda, R. O., & Hart, P. E. (2006). 2nd Edition, Pattern classification. John Wiley & Sons.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 3 15
Presentation - -
Project 1 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 20
Final Exam/Final Jury 1 35
Toplam 6 100
Percentage of Semester Work
Percentage of Final Work 100
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Has adequate knowledge in mathematics, science, and computer engineering-specific subjects; uses theoretical and practical knowledge in these areas to solve complex engineering problems.
2 Identifies, defines, formulates, and solves complex engineering problems; selects and applies appropriate analysis and modeling methods for this purpose.
3 Designs a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions; applies modern design methods for this purpose.
4 Develops, selects, and uses modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; uses information technologies effectively.
5 Designs experiments, conducts experiments, collects data, analyzes and interprets results for the investigation of complex engineering problems or research topics specific to the discipline of computer engineering.
6 Works effectively in disciplinary and multidisciplinary teams; gains the ability to work individually.
7 Communicates effectively in Turkish, both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions.
8 Knows at least one foreign language; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions.
9 Has awareness of the necessity of lifelong learning; accesses information, follows developments in science and technology, and continuously improves oneself.
10 Acts in accordance with ethical principles and has awareness of professional and ethical responsibility.
11 Has knowledge about the standards used in computer engineering applications.
12 Has knowledge about workplace practices such as project management, risk management, and change management. X
13 Gains awareness about entrepreneurship and innovation.
14 Has knowledge about sustainable development.
15 Has knowledge about the health, environmental, and safety impacts of computer engineering applications in universal and societal dimensions and the contemporary issues reflected in the field of engineering.
16 Gains awareness of the legal consequences of engineering solutions.
17 Analyzes, designs, and expresses numerical computation and digital representation systems.
18 Uses programming languages and appropriate computer engineering concepts to solve computational problems.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 3 48
Presentation/Seminar Prepration
Project 1 20 20
Report
Homework Assignments 3 3 9
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 3 3
Prepration of Final Exams/Final Jury 1 3 3
Total Workload 131