DEPARTMENT OF SOFTWARE ENGINEERING (ENGLISH)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

1413002003

Ders İsmi:

Computer Vision

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Department Elective

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi Adem ÖZYAVAŞ

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:

- Learning the concept of model checking
- Having insight on the theoretical background of model checking
- Learning program verification using model checking

Course Content:

BLG 633E - Model Checking for Software Systems
Dersin Amaçları
- Learning the concept of model checking
- Having insight on the theoretical background of model checking
- Learning program verification using model checking

Dersin Tanımı
During the course, model checking methods will be covered that can be used in program verification and during specification and design stages of software development. Course will begin with introduction of the concept of model checking and theoretical background of modern model checking methods. Later, basic SMV, SPIN and UPPAAL examples will be used to demonstrate program verification and finally some formal languages that are integrated to modern programming languages will be examined

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Karmaşık bir sistemi süreci, cihaz veya standartlar ve koşullar altında, belirli kalitede tasarım tasarlama becerileri; bu amaçla modern tasarım becerini uygulama becerisi.
2) Understanding computer vision hardware and software elements
3) computer vision systems
4) Developing and coding image processing algorithms
5) Designing image processing systems for industry
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Introduction to computer vision	Relevant section in resources
2)	Hardware and software architecture of computer vision system	Relevant section in resources
2)	Feature extraction for classification applications in computer vision	Relevant section in resources
4)	Expressing the picture as a matrix and neighborhood operations	Relevant section in resources
5)	Image processing for visual inspection and quality systems	Relevant section in resources
6)	Fundamentals of 3D image processing	Relevant section in resources
6)	Edge and corner finding algorithms	Relevant section in resources
6)	Processing and using black and white, grayscale and color images	Relevant section in resources
7)	Thresholding, image histogram and noise removal methods	Relevant section in resources
7)	Image analysis for pattern recognition	Relevant section in resources
9)	Midterm
10)	Feature extraction for classification applications in computer vision	Relevant section in resources
11)	Image processing for visual inspection and quality systems	Relevant section in resources
12)	Fundamentals of 3D image processing	Relevant section in resources
13)	Industry practices and student presentations	Relevant section in resources
14)	Sample applications and student presentations	Relevant section in resources
15)

Sources

Course Notes / Textbooks:	Ders notları
References:	Lecture notes

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	1	2	3	4
Program Outcomes
1) Competent knowledge of mathematics, science and technology, and computer engineering; ability to apply this knowledge to engineering solutions.
2) Skills to design and conduct experiments, collect data, analyze and interpret results.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4) Ability to develop, select and use modern techniques and tools required for analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
5) Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics.
6) Ability to work effectively in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in Turkish, both orally and in writing; Knowledge of at least one foreign language; the ability to write and understand written reports effectively, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the necessity of lifelong learning; the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
9) Acting in accordance with ethical principles, professional and ethical responsibility awareness; information about standards used in engineering applications.
10) Information about business life practices such as project management, risk management and change management; awareness of entrepreneurship, innovation; information about sustainable development.
11) Knowledge about the universal and social effects of engineering applications on health, environment and safety and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions.

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Competent knowledge of mathematics, science and technology, and computer engineering; ability to apply this knowledge to engineering solutions.
2)	Skills to design and conduct experiments, collect data, analyze and interpret results.
3)	Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools required for analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
5)	Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics.
6)	Ability to work effectively in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7)	Ability to communicate effectively in Turkish, both orally and in writing; Knowledge of at least one foreign language; the ability to write and understand written reports effectively, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8)	Awareness of the necessity of lifelong learning; the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
9)	Acting in accordance with ethical principles, professional and ethical responsibility awareness; information about standards used in engineering applications.
10)	Information about business life practices such as project management, risk management and change management; awareness of entrepreneurship, innovation; information about sustainable development.
11)	Knowledge about the universal and social effects of engineering applications on health, environment and safety and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Semester Final Exam	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	13	3	39
Study Hours Out of Class	14	9	126
Midterms	1	2	2
Final	1	2	2
Total Workload			169